Package evaluation to test SDDP on Julia 1.13.0-DEV.1342 (4ff19f0352*) started at 2025-10-19T18:24:16.864 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.17s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [f4570300] + SDDP v1.13.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.2 [d1d4a3ce] + BitFlags v0.1.9 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [f0e56b4a] + ConcurrentUtilities v2.5.0 [864edb3b] + DataStructures v0.19.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v1.2.2 [cd3eb016] + HTTP v1.10.19 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.7.1 ⌅ [682c06a0] + JSON v0.21.4 [0f8b85d8] + JSON3 v1.14.3 [4076af6c] + JuMP v1.29.1 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.45.0 [739be429] + MbedTLS v1.1.9 [d8a4904e] + MutableArithmetics v1.6.6 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.5.0 [bac558e1] + OrderedCollections v1.8.1 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.13.0 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.6.1 [1e83bf80] + StaticArraysCore v1.4.3 [10745b16] + Statistics v1.11.1 [856f2bd8] + StructTypes v1.11.0 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.6.1 [6e34b625] + Bzip2_jll v1.0.9+0 [c8ffd9c3] + MbedTLS_jll v2.28.10+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [14a3606d] + MozillaCACerts_jll v2025.9.9 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.15.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 5.54s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 50.74s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_68oJKY/Project.toml` [87dc4568] HiGHS v1.19.3 [b6b21f68] Ipopt v1.11.0 ⌅ [682c06a0] JSON v0.21.4 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.1 [f4570300] SDDP v1.13.0 [10745b16] Statistics v1.11.1 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [44cfe95a] Pkg v1.13.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_68oJKY/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [6e4b80f9] BenchmarkTools v1.6.2 [d1d4a3ce] BitFlags v0.1.9 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.31.0 [3da002f7] ColorTypes v0.12.1 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.1 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [f0e56b4a] ConcurrentUtilities v2.5.0 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.1 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Testing Running tests... [ Info: Experimental.jl [ Info: fetching remote ref https://jump.dev/MathOptFormat/schemas/mof.1.schema.json [ Info: Inner.jl Node: 3 - elapsed time: 0.12 plus 18.7 for vertex selection. Node: 2 - elapsed time: 0.04 plus 0.02 for vertex selection. Node: 1 - elapsed time: 0.04 plus 0.02 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 18.936505272999998 ┌ Warning: You must select an optimizer for performing vertex selection. └ @ SDDP.Inner ~/.julia/packages/SDDP/39RYL/src/Inner.jl:1048 Node: 19 - elapsed time: 0.1 plus 0.06 for vertex selection. Node: 18 - elapsed time: 0.2 plus 0.07 for vertex selection. Node: 17 - elapsed time: 0.19 plus 0.06 for vertex selection. Node: 16 - elapsed time: 0.2 plus 0.07 for vertex selection. Node: 15 - elapsed time: 0.2 plus 0.06 for vertex selection. Node: 14 - elapsed time: 0.2 plus 0.06 for vertex selection. Node: 13 - elapsed time: 0.23 plus 0.08 for vertex selection. Node: 12 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 11 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 10 - elapsed time: 0.2 plus 0.07 for vertex selection. Node: 9 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 8 - elapsed time: 0.2 plus 0.07 for vertex selection. Node: 7 - elapsed time: 0.2 plus 0.06 for vertex selection. Node: 6 - elapsed time: 0.2 plus 0.07 for vertex selection. Node: 5 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 4 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 3 - elapsed time: 0.22 plus 0.07 for vertex selection. Node: 2 - elapsed time: 0.21 plus 0.07 for vertex selection. Node: 1 - elapsed time: 0.21 plus 0.06 for vertex selection. Selection removed 500 vertices [ Info: MSPFormat.jl [ Info: algorithm.jl ┌ Warning: Unable to recover in direct mode! Remove `direct = true` when creating the policy graph. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/algorithm.jl:401 [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.AffExpr in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [2, 2] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- † 1 0.000000e+00 0.000000e+00 5.897093e-02 4 1 3 0.000000e+00 0.000000e+00 7.857800e-01 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.857800e-01 total solves : 12 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 1 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [4, 4] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.100000e+05 1.075000e+05 2.449703e-02 9 1 20 7.500000e+04 1.075000e+05 6.706691e-01 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.706691e-01 total solves : 204 best bound : 1.075000e+05 simulation ci : 8.268750e+04 ± 1.084410e+04 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/algorithm.jl:1181 ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/algorithm.jl:1181 [ Info: binary_expansion.jl [ Info: deterministic_equivalent.jl [ Info: modeling_aids.jl ┌ Warning: Budget for nodes is less than the number of stages. Using one node per stage. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/modeling_aids.jl:125 [ Info: user_interface.jl [ Info: backward_sampling_schemes.jl [ Info: bellman_functions.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.138889e+01 1.061856e+00 12 1 10 2.500000e+00 3.361111e+01 1.090491e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.090491e+00 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.083333e+01 1.336408e-02 12 1 10 2.500000e+00 3.361111e+01 3.651500e-02 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.651500e-02 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 8.960962e-03 46 1 50 0.000000e+00 1.191663e+02 7.200198e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.200198e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 1.069593e-02 46 1 50 0.000000e+00 1.191663e+02 5.047410e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.047410e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: duality_handlers.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 1.00000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 11] JuMP.AffExpr in MOI.LessThan{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [3, 7] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 7] JuMP.VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -4.650000e+01 -7.053967e+01 3.948255e+00 103 1 3S -5.785826e+01 -6.755367e+01 6.661501e+00 309 1 4S -6.230988e+01 -6.688020e+01 7.721124e+00 412 1 6S -6.064080e+01 -6.678327e+01 8.845124e+00 618 1 7S -6.493167e+01 -6.677772e+01 9.875348e+00 721 1 17S -6.068889e+01 -6.677644e+01 1.502479e+01 1751 1 27S -6.068889e+01 -6.677644e+01 2.029808e+01 2781 1 37S -7.668889e+01 -6.677644e+01 2.635861e+01 3811 1 47S -5.768889e+01 -6.677644e+01 3.218353e+01 4841 1 57S -8.368889e+01 -6.677644e+01 3.794726e+01 5871 1 67S -7.668889e+01 -6.677644e+01 4.376267e+01 6901 1 77S -6.468889e+01 -6.677644e+01 4.927492e+01 7931 1 87S -6.068889e+01 -6.677644e+01 5.522763e+01 8961 1 97S -6.068889e+01 -6.677644e+01 6.136755e+01 9991 1 100 -8.368889e+01 -6.677644e+01 6.257495e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.257495e+01 total solves : 10300 best bound : -6.677644e+01 simulation ci : -5.960112e+01 ± 3.154656e+00 numeric issues : 0 ------------------------------------------------------------------- ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit https://github.com/coin-or/Ipopt ****************************************************************************** [ Info: forward_passes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 3.000000e+00 6.000000e+00 1.805067e-03 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.805067e-03 total solves : 8 best bound : 6.000000e+00 simulation ci : 3.000000e+00 ± NaN numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/algorithm.jl:1181 [ Info: local_improvement_search.jl [ Info: exp = 15 [ Info: OA(exp) = 220 [ Info: piecewise = 7 [ Info: OA(piecewise) = 6 [ Info: squared = 3 [ Info: OA(squared) = 16 [ Info: parallel_schemes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+00 6.000000e+00 3.189282e+02 2 2 20 3.000000e+00 6.000000e+00 3.250038e+02 40 2 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.250038e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 6.100000e+00 ± 1.081978e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/algorithm.jl:1181 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : true options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [4e+00, 4e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 5.000000e+00 6.000000e+00 2.974789e-01 48 1 20 9.000000e+00 6.000000e+00 5.648289e-01 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.648289e-01 total solves : 162 best bound : 6.000000e+00 simulation ci : 5.900000e+00 ± 9.633534e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: risk_measures.jl ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/risk_measures.jl:528 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 5.839825e-03 4 1 50 0.000000e+00 0.000000e+00 2.543859e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 2.543859e-01 total solves : 200 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/39RYL/src/plugins/stopping_rules.jl:132 [ Info: threaded.jl [ Info: value_functions.jl [ Info: visualization.jl test_SpaghettiPlot: Test Failed at /home/pkgeval/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:49 Expression: read("test.html", String) == read(control, String) Evaluated: "\n\n\n\n\n \n \n \n\n\n\n
\n \n\n\n\n\n" == "\n\n\n\n\n \n \n \n\n\n\n
\n \n\n\n\n\n" Stacktrace: [1] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:753 [inlined] [2] test_SpaghettiPlot() @ Main.TestVisualization ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:49 [3] macro expansion @ ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:17 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1961 [inlined] [5] runtests() @ Main.TestVisualization ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:17 ┌ Warning: `SDDP.save` is deprecated. Use `SDDP.plot` instead. │ caller = test_SpaghettiPlot() at visualization.jl:51 └ @ Core ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:51 test_SpaghettiPlot: Test Failed at /home/pkgeval/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:55 Expression: read("test.html", String) == read(control, String) Evaluated: "\n\n\n\n\n \n \n \n\n\n\n
\n \n\n\n\n\n" == "\n\n\n\n\n \n \n \n\n\n\n
\n \n\n\n\n\n" Stacktrace: [1] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:753 [inlined] [2] test_SpaghettiPlot() @ Main.TestVisualization ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:55 [3] macro expansion @ ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:17 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1961 [inlined] [5] runtests() @ Main.TestVisualization ~/.julia/packages/SDDP/39RYL/test/visualization/visualization.jl:17 [ Info: FAST_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+00] bounds range [8e+00, 8e+00] rhs range [6e+00, 6e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -2.000000e+01 -1.000000e+01 6.677339e+00 5 1 20 0.000000e+00 -1.000000e+01 7.338537e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.338537e+00 total solves : 104 best bound : -1.000000e+01 simulation ci : -1.100000e+01 ± 4.474009e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: FAST_production_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -5.320000e+00 -2.396000e+01 3.085685e-02 52 1 10 -2.396000e+01 -2.396000e+01 3.870583e-02 92 1 15 -4.260000e+01 -2.396000e+01 4.713988e-02 132 1 20 -2.396000e+01 -2.396000e+01 5.648994e-02 172 1 25 -5.320000e+00 -2.396000e+01 6.868100e-02 224 1 30 -5.320000e+00 -2.396000e+01 7.974696e-02 264 1 35 -2.396000e+01 -2.396000e+01 9.159803e-02 304 1 40 -2.396000e+01 -2.396000e+01 1.048729e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.048729e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 451ms / 19.1% 11.8MiB / 58.8% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 51.1ms 59.1% 1.28ms 5.22MiB 75.0% 134KiB solve_subproblem 160 26.5ms 30.7% 166μs 721KiB 10.1% 4.51KiB get_dual_solution 160 1.31ms 1.5% 8.20μs 185KiB 2.6% 1.16KiB prepare_backward_pass 160 61.5μs 0.1% 385ns 0.00B 0.0% 0.00B forward_pass 40 25.4ms 29.4% 634μs 1.56MiB 22.4% 39.9KiB solve_subproblem 120 23.3ms 27.0% 194μs 1.39MiB 20.0% 11.9KiB get_dual_solution 120 41.7μs 0.0% 347ns 13.1KiB 0.2% 112B sample_scenario 40 367μs 0.4% 9.17μs 22.3KiB 0.3% 572B calculate_bound 40 10.0ms 11.5% 249μs 182KiB 2.5% 4.54KiB get_dual_solution 40 14.9μs 0.0% 372ns 4.38KiB 0.1% 112B get_dual_solution 36 12.9μs 0.0% 359ns 3.94KiB 0.1% 112B ──────────────────────────────────────────────────────────────────────────────────── ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -2.396000e+01 -2.396000e+01 6.173897e-02 52 1 10 -2.396000e+01 -2.396000e+01 7.114410e-02 92 1 15 -2.396000e+01 -2.396000e+01 8.197403e-02 132 1 20 -4.260000e+01 -2.396000e+01 9.499002e-02 172 1 25 -5.320000e+00 -2.396000e+01 1.118350e-01 224 1 30 -2.396000e+01 -2.396000e+01 1.283021e-01 264 1 35 -2.396000e+01 -2.396000e+01 1.472661e-01 304 1 40 -5.320000e+00 -2.396000e+01 1.682401e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.682401e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 176ms / 88.5% 13.7MiB / 93.6% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 117ms 75.4% 2.93ms 11.1MiB 86.4% 283KiB solve_subproblem 160 29.2ms 18.8% 182μs 722KiB 5.5% 4.51KiB get_dual_solution 160 1.41ms 0.9% 8.79μs 185KiB 1.4% 1.16KiB prepare_backward_pass 160 73.8μs 0.0% 461ns 0.00B 0.0% 0.00B forward_pass 40 26.3ms 16.9% 656μs 1.56MiB 12.2% 39.9KiB solve_subproblem 120 23.8ms 15.3% 198μs 1.39MiB 10.9% 11.9KiB get_dual_solution 120 48.5μs 0.0% 404ns 13.1KiB 0.1% 112B sample_scenario 40 458μs 0.3% 11.5μs 22.5KiB 0.2% 575B calculate_bound 40 12.0ms 7.7% 300μs 183KiB 1.4% 4.58KiB get_dual_solution 40 22.5μs 0.0% 563ns 4.38KiB 0.0% 112B get_dual_solution 36 12.9μs 0.0% 358ns 3.94KiB 0.0% 112B ──────────────────────────────────────────────────────────────────────────────────── [ Info: FAST_quickstart.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 4] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 5e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 -2.500000e+00 1.807499e-01 5 1 2 -2.500000e+00 -2.000000e+00 1.827960e-01 14 1 3 -1.000000e+00 -2.000000e+00 1.837349e-01 19 1 4 -1.000000e+00 -2.000000e+00 1.845429e-01 24 1 5 -1.000000e+00 -2.000000e+00 1.853759e-01 29 1 6 -3.000000e+00 -2.000000e+00 1.861780e-01 34 1 7 -1.000000e+00 -2.000000e+00 1.870229e-01 39 1 8 -1.000000e+00 -2.000000e+00 1.880898e-01 44 1 9 -3.000000e+00 -2.000000e+00 1.889360e-01 49 1 10 -1.000000e+00 -2.000000e+00 1.898189e-01 54 1 11 -3.000000e+00 -2.000000e+00 1.906819e-01 59 1 12 -3.000000e+00 -2.000000e+00 1.915998e-01 64 1 13 -1.000000e+00 -2.000000e+00 1.925189e-01 69 1 14 -1.000000e+00 -2.000000e+00 1.934350e-01 74 1 15 -3.000000e+00 -2.000000e+00 1.943710e-01 79 1 16 -1.000000e+00 -2.000000e+00 1.953239e-01 84 1 17 -3.000000e+00 -2.000000e+00 1.962829e-01 89 1 18 -3.000000e+00 -2.000000e+00 1.972780e-01 94 1 19 -1.000000e+00 -2.000000e+00 1.982698e-01 99 1 20 -3.000000e+00 -2.000000e+00 1.992900e-01 104 1 21 -1.000000e+00 -2.000000e+00 2.010329e-01 113 1 22 -1.000000e+00 -2.000000e+00 2.020478e-01 118 1 23 -3.000000e+00 -2.000000e+00 2.030780e-01 123 1 24 -3.000000e+00 -2.000000e+00 2.041399e-01 128 1 25 -1.000000e+00 -2.000000e+00 2.052050e-01 133 1 26 -3.000000e+00 -2.000000e+00 2.062988e-01 138 1 27 -3.000000e+00 -2.000000e+00 2.073538e-01 143 1 28 -1.000000e+00 -2.000000e+00 2.084870e-01 148 1 29 -3.000000e+00 -2.000000e+00 2.096219e-01 153 1 30 -3.000000e+00 -2.000000e+00 2.107840e-01 158 1 31 -1.000000e+00 -2.000000e+00 2.119648e-01 163 1 32 -1.000000e+00 -2.000000e+00 2.131588e-01 168 1 33 -1.000000e+00 -2.000000e+00 2.143719e-01 173 1 34 -3.000000e+00 -2.000000e+00 2.155938e-01 178 1 35 -1.000000e+00 -2.000000e+00 2.168238e-01 183 1 36 -3.000000e+00 -2.000000e+00 2.180920e-01 188 1 37 -1.000000e+00 -2.000000e+00 2.193599e-01 193 1 38 -1.000000e+00 -2.000000e+00 2.206259e-01 198 1 39 -1.000000e+00 -2.000000e+00 2.219260e-01 203 1 40 -1.000000e+00 -2.000000e+00 2.232418e-01 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.232418e-01 total solves : 208 best bound : -2.000000e+00 simulation ci : -1.812500e+00 ± 3.171441e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: Hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+00] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.000000e+01 1.882708e+01 2.727330e-01 51 1 25 1.560330e+02 2.260386e+02 1.332742e+00 4203 1 30 2.138334e+03 2.336430e+02 2.528759e+00 7674 1 38 8.025312e+02 2.352957e+02 3.643370e+00 10194 1 47 3.025787e+02 2.359215e+02 4.765626e+00 12321 1 58 4.114170e+01 2.360915e+02 5.785993e+00 13734 1 63 1.493193e+03 2.362190e+02 7.153608e+00 15909 1 73 3.670177e+02 2.363045e+02 8.317711e+00 17655 1 77 1.654348e+02 2.363524e+02 9.463737e+00 19191 1 100 4.969839e+02 2.364135e+02 1.347141e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.347141e+01 total solves : 23928 best bound : 2.364135e+02 simulation ci : 2.345669e+02 ± 6.032770e+01 numeric issues : 0 ------------------------------------------------------------------- On average, 2.1 units of thermal are used in the first stage. [ Info: StochDynamicProgramming.jl_multistock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 3 scenarios : 1.43489e+07 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [13, 13] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 5e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.977586e+00 -4.446713e+00 8.354309e-01 1400 1 20 -4.764789e+00 -4.394789e+00 1.249491e+00 2800 1 30 -4.672487e+00 -4.377000e+00 1.566670e+00 4200 1 40 -4.483495e+00 -4.370632e+00 1.895600e+00 5600 1 50 -4.167321e+00 -4.364999e+00 2.238298e+00 7000 1 60 -4.362455e+00 -4.358864e+00 2.584293e+00 8400 1 70 -4.849916e+00 -4.355337e+00 2.931815e+00 9800 1 80 -4.861568e+00 -4.353006e+00 3.285412e+00 11200 1 90 -4.268264e+00 -4.350407e+00 3.641439e+00 12600 1 100 -4.539897e+00 -4.348641e+00 4.000028e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.000028e+00 total solves : 14000 best bound : -4.348641e+00 simulation ci : -4.325070e+00 ± 8.068871e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StochDynamicProgramming.jl_stock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 1 scenarios : 1.00000e+05 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 2e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -1.671715e+00 -1.476962e+00 4.494381e-01 1050 1 20 -1.529197e+00 -1.471817e+00 5.387001e-01 1600 1 30 -1.410768e+00 -1.471408e+00 7.347109e-01 2650 1 40 -1.596461e+00 -1.471258e+00 8.324301e-01 3200 1 50 -1.002277e+00 -1.471216e+00 1.037459e+00 4250 1 60 -1.085156e+00 -1.471164e+00 1.141942e+00 4800 1 70 -1.391746e+00 -1.471164e+00 1.355257e+00 5850 1 80 -1.448703e+00 -1.471132e+00 1.468921e+00 6400 1 90 -1.488989e+00 -1.471087e+00 1.688456e+00 7450 1 100 -1.564260e+00 -1.471075e+00 1.810046e+00 8000 1 110 -1.738157e+00 -1.471075e+00 1.923632e+00 8550 1 120 -1.591292e+00 -1.471075e+00 2.049454e+00 9100 1 130 -1.271481e+00 -1.471075e+00 2.169904e+00 9650 1 140 -1.249746e+00 -1.471075e+00 2.296779e+00 10200 1 150 -1.536222e+00 -1.471075e+00 2.425249e+00 10750 1 160 -1.565422e+00 -1.471075e+00 2.564020e+00 11300 1 170 -1.631076e+00 -1.471075e+00 2.698920e+00 11850 1 180 -1.494909e+00 -1.471075e+00 2.836439e+00 12400 1 182 -9.083563e-01 -1.471075e+00 2.860966e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.860966e+00 total solves : 12510 best bound : -1.471075e+00 simulation ci : -1.462065e+00 ± 2.699238e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_2stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 4 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+06] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.455904e+05 3.147347e+05 2.443099e-02 54 1 20 3.336455e+05 3.402383e+05 3.838992e-02 104 1 30 3.993519e+05 3.403155e+05 5.175805e-02 158 1 40 3.337559e+05 3.403155e+05 6.348395e-02 208 1 48 3.337559e+05 3.403155e+05 7.503891e-02 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.503891e-02 total solves : 248 best bound : 3.403155e+05 simulation ci : 1.298444e+08 ± 1.785864e+08 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_3stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+05] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.403329e+05 3.509666e+05 3.928590e-02 92 1 20 4.506600e+05 4.054833e+05 6.304002e-02 172 1 30 3.959476e+05 4.067125e+05 8.381987e-02 264 1 40 4.497721e+05 4.067125e+05 1.036379e-01 344 1 47 3.959476e+05 4.067125e+05 1.206889e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.206889e-01 total solves : 400 best bound : 4.067125e+05 simulation ci : 2.696242e+07 ± 3.645299e+07 numeric issues : 0 ------------------------------------------------------------------- [ Info: agriculture_mccardle_farm.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 10 state variables : 4 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [24, 24] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 6] VariableRef in MOI.GreaterThan{Float64} : [20, 20] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 8e+01] objective range [1e+00, 1e+03] bounds range [6e+01, 6e+01] rhs range [2e+02, 3e+03] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 8.316000e+03 0.000000e+00 6.878355e+00 14 1 40 2.308500e+03 4.074139e+03 7.716649e+00 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.716649e+00 total solves : 776 best bound : 4.074139e+03 simulation ci : 4.224313e+03 ± 6.692189e+02 numeric issues : 0 ------------------------------------------------------------------- [ Info: air_conditioning.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 7.000000e+04 6.250000e+04 2.138621e+00 8 1 7L 5.500000e+04 6.250000e+04 3.199394e+00 68 1 16L 6.000000e+04 6.250000e+04 4.367379e+00 140 1 20L 6.000000e+04 6.250000e+04 5.115343e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.115343e+00 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.475000e+04 ± 7.336233e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 1.989794e-02 8 1 15 5.500000e+04 6.250000e+04 1.054216e+00 132 1 20 4.000000e+04 6.250000e+04 1.406786e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.406786e+00 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.950000e+04 ± 8.933885e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). [ Info: air_conditioning_forward.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [1e+02, 3e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 6.396103e-02 5 1 10 4.000000e+04 6.250000e+04 7.611959e-01 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.611959e-01 total solves : 50 best bound : 6.250000e+04 simulation ci : 5.450000e+04 ± 1.135842e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 9.000000e+00 3.424370e-01 6 1 20L 9.000000e+00 9.000000e+00 6.481271e-01 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.481271e-01 total solves : 123 best bound : 9.000000e+00 simulation ci : 8.850000e+00 ± 2.940000e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_simple.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -1.109375e+01 2.605769e-01 1.093994e+00 87 1 10 -1.109375e+01 2.605769e-01 1.108445e+00 142 1 15 3.105797e+00 5.434132e-01 1.122934e+00 197 1 20 -2.463349e+01 1.503415e+00 1.137420e+00 252 1 25 -1.421085e-14 1.514085e+00 1.152500e+00 307 1 30 4.864000e+01 1.514085e+00 3.342525e+00 394 1 35 4.864000e+01 1.514085e+00 3.358926e+00 449 1 40 -8.870299e+00 1.514085e+00 3.377055e+00 504 1 45 -1.428571e+00 1.514085e+00 3.396144e+00 559 1 48 -1.428571e+00 1.514085e+00 3.409378e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.409378e+00 total solves : 592 best bound : 1.514085e+00 simulation ci : 2.494033e+00 ± 5.472486e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_stagewise.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.395796e+01 1.428818e+00 1.007103e+00 278 1 20 1.440356e+01 1.278425e+00 1.051908e+00 428 1 30 8.388546e+00 1.278425e+00 1.121994e+00 706 1 40 6.666667e-03 1.278410e+00 1.165267e+00 856 1 50 -5.614035e+00 1.278410e+00 1.237370e+00 1134 1 60 1.426676e+01 1.278410e+00 1.286908e+00 1284 1 64 1.261296e+01 1.278410e+00 1.307357e+00 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.307357e+00 total solves : 1344 best bound : 1.278410e+00 simulation ci : 8.172580e-01 ± 5.385320e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.111809e+00 1.278488e+00 1.002309e-01 278 1 20 1.111084e+01 1.278410e+00 1.536391e-01 428 1 30 2.293779e+01 1.278410e+00 2.408719e-01 706 1 40 1.426676e+01 1.278410e+00 3.250430e-01 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.250430e-01 total solves : 856 best bound : 1.278410e+00 simulation ci : 3.654300e+00 ± 6.176856e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: belief.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 4 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.787277e+00 9.346930e+00 6.096220e+00 900 1 20 6.374753e+00 1.361934e+01 6.467172e+00 1720 1 30 2.848217e+01 1.624016e+01 7.383451e+00 3036 1 40 1.973944e+01 1.776547e+01 8.372853e+00 4192 1 50 4.000000e+00 1.889360e+01 9.278954e+00 5020 1 60 1.142478e+01 1.907862e+01 1.022928e+01 5808 1 70 9.386421e+00 1.961295e+01 1.119182e+01 6540 1 80 5.667851e+01 1.890911e+01 1.195551e+01 7088 1 90 3.740597e+01 1.993139e+01 1.366111e+01 8180 1 100 9.867183e+00 2.001688e+01 1.441051e+01 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.441051e+01 total solves : 8664 best bound : 2.001688e+01 simulation ci : 2.301336e+01 ± 4.670816e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: biobjective_hydro.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 3.196507e+00 36 1 10 0.000000e+00 0.000000e+00 3.246698e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.246698e+00 total solves : 360 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 7] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.500000e+02 5.500000e+02 7.430077e-03 407 1 10 2.850000e+02 5.728212e+02 7.220602e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.220602e-02 total solves : 731 best bound : 5.728212e+02 simulation ci : 6.480000e+02 ± 1.400040e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 13] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.150000e+02 3.347014e+02 7.366180e-03 778 1 10 2.825000e+02 3.465177e+02 7.343507e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.343507e-02 total solves : 1102 best bound : 3.465177e+02 simulation ci : 3.598954e+02 ± 6.281469e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 20] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.387500e+02 1.994007e+02 7.740974e-03 1149 1 10 2.587500e+02 2.052799e+02 7.121897e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.121897e-02 total solves : 1473 best bound : 2.052799e+02 simulation ci : 2.206923e+02 ± 2.764045e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 24] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.375000e+02 4.637735e+02 8.687973e-03 1520 1 10 2.875000e+02 4.661908e+02 8.095002e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.095002e-02 total solves : 1844 best bound : 4.661908e+02 simulation ci : 5.075000e+02 ± 1.503394e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 30] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.112500e+02 1.129545e+02 8.080959e-03 1891 1 10 1.000000e+02 1.129771e+02 7.230592e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.230592e-02 total solves : 2215 best bound : 1.129771e+02 simulation ci : 1.068750e+02 ± 2.168477e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 34] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.562500e+02 2.788383e+02 8.311987e-03 2262 1 10 1.625000e+02 2.794553e+02 7.873702e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.873702e-02 total solves : 2586 best bound : 2.794553e+02 simulation ci : 2.690625e+02 ± 6.720434e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 37] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.810804e+02 4.073537e+02 8.896112e-03 2633 1 10 5.487500e+02 4.077574e+02 8.379793e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.379793e-02 total solves : 2957 best bound : 4.077574e+02 simulation ci : 3.863418e+02 ± 9.936379e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 43] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.718750e+02 5.198033e+02 9.374142e-03 3004 1 10 6.771875e+02 5.210100e+02 8.426714e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.426714e-02 total solves : 3328 best bound : 5.210100e+02 simulation ci : 5.831217e+02 ± 1.295425e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 50] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.812500e+01 5.720558e+01 8.485079e-03 3375 1 10 5.312500e+01 5.938345e+01 7.323313e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.323313e-02 total solves : 3699 best bound : 5.938345e+01 simulation ci : 6.187500e+01 ± 1.306667e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: booking_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [10, 10] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.GreaterThan{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 6] VariableRef in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.ZeroOne : [5, 5] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 8.000000e+00 9.440450e+00 1.407579e+00 235 1 10 1.000000e+01 9.159200e+00 1.912521e+00 310 1 15 1.000000e+01 9.159200e+00 2.455612e+00 385 1 20 1.000000e+01 9.159200e+00 2.981193e+00 460 1 25 1.000000e+01 9.159200e+00 5.961513e+00 695 1 30 4.000000e+00 9.159200e+00 6.461573e+00 770 1 35 1.000000e+01 9.159200e+00 6.957160e+00 845 1 40 1.000000e+01 9.159200e+00 7.518554e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.518554e+00 total solves : 920 best bound : 9.159200e+00 simulation ci : 7.200000e+00 ± 8.485598e-01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 2.16000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [18, 18] AffExpr in MOI.EqualTo{Float64} : [4, 4] AffExpr in MOI.GreaterThan{Float64} : [4, 4] AffExpr in MOI.LessThan{Float64} : [12, 12] VariableRef in MOI.EqualTo{Float64} : [4, 4] VariableRef in MOI.GreaterThan{Float64} : [9, 10] VariableRef in MOI.LessThan{Float64} : [10, 10] VariableRef in MOI.ZeroOne : [9, 9] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+00, 2e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.000000e+00 6.959189e+00 1.428133e+00 510 1 20 1.000000e+01 6.834387e+00 3.209162e+00 720 1 30 7.000000e+00 6.834387e+00 7.407116e+00 1230 1 40 1.000000e+01 6.823805e+00 9.091121e+00 1440 1 50 3.000000e+00 6.823805e+00 1.338317e+01 1950 1 60 2.000000e+00 6.823805e+00 1.516717e+01 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.516717e+01 total solves : 2160 best bound : 6.823805e+00 simulation ci : 6.183333e+00 ± 6.694539e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: generation_expansion.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.299676e+06 2.074407e+06 1.409164e+01 920 1 20 6.049875e+06 2.075240e+06 1.694904e+01 1340 1 30 5.496647e+05 2.078257e+06 3.019448e+01 2260 1 40 3.985383e+04 2.078257e+06 3.294063e+01 2680 1 50 2.994548e+05 2.078257e+06 4.627797e+01 3600 1 60 3.799457e+06 2.078257e+06 4.923491e+01 4020 1 61 3.549665e+06 2.078257e+06 4.951689e+01 4062 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.951689e+01 total solves : 4062 best bound : 2.078257e+06 simulation ci : 2.437601e+06 ± 5.082681e+05 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10L 2.049870e+06 2.079457e+06 3.481290e+01 920 1 20L 2.799668e+06 2.079457e+06 5.724232e+01 1340 1 30L 3.799443e+06 2.079457e+06 8.888291e+01 2260 1 40L 4.299882e+06 2.079457e+06 1.084416e+02 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.084416e+02 total solves : 2680 best bound : 2.079457e+06 simulation ci : 1.602238e+06 ± 4.944385e+05 numeric issues : 0 ------------------------------------------------------------------- [ Info: hydro_valley.jl [ Info: infinite_horizon_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.188534e+02 2.317185e+00 1914 1 200 0.000000e+00 1.191645e+02 2.730094e+00 3840 1 300 7.500000e+01 1.191666e+02 3.140990e+00 5738 1 328 2.500000e+00 1.191667e+02 3.222634e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.222634e+00 total solves : 6034 best bound : 1.191667e+02 simulation ci : 2.272866e+01 ± 3.596240e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 128.14 ± 13.91 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.191232e+02 4.956422e-01 2806 1 200 0.000000e+00 1.191666e+02 9.172981e-01 4749 1 287 5.000000e+00 1.191667e+02 1.240267e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.240267e+00 total solves : 5662 best bound : 1.191667e+02 simulation ci : 2.112369e+01 ± 3.684376e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 122.02 ± 14.06 [ Info: infinite_horizon_trivial.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 2.000000e+01 1.998872e+01 1.393480e-01 1033 1 20 8.000000e+00 2.000000e+01 1.676588e-01 1209 1 30 1.200000e+01 2.000000e+01 3.078690e-01 2304 1 40 3.000000e+01 2.000000e+01 3.939109e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.939109e-01 total solves : 2594 best bound : 2.000000e+01 simulation ci : 1.970000e+01 ± 4.721453e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: inner_hydro_1d.jl Building and solving primal outer model for lower bounds ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 4 state variables : 1 scenarios : 1.00000e+03 existing cuts : false options solver : serial mode risk measure : A convex combination of 0.5 * SDDP.Expectation() + 0.5 * SDDP.AVaR(0.2) sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+01] bounds range [2e+01, 2e+02] rhs range [8e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.948878e+03 2.847167e+03 8.950806e-02 35 1 10 7.500000e+02 2.935390e+03 1.614261e-01 350 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.614261e-01 total solves : 350 best bound : 2.935390e+03 simulation ci : 1.544902e+03 ± 5.533339e+02 numeric issues : 0 ------------------------------------------------------------------- Building and solving inner model for upper bounds: Node: 3 - elapsed time: 0.31 plus 0.71 for vertex selection. Node: 2 - elapsed time: 0.03 plus 0.01 for vertex selection. Node: 1 - elapsed time: 0.03 plus 0.01 for vertex selection. First-stage upper bound: 2969.680973503913 Total time for upper bound: 1.1035654959999999 Bounds: Risk-neutral confidence interval: 1411.99 ± 82.02 Risk-adjusted lower bound: 2935.39 Risk-adjusted upper bound: 2969.68 [ Info: no_strong_duality.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.000000e+00 1.500000e+00 6.659985e-03 3 1 40 2.000000e+00 2.000000e+00 1.073270e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.073270e-01 total solves : 604 best bound : 2.000000e+00 simulation ci : 2.150000e+00 ± 5.038753e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: objective_state_newsvendor.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.675000e+00 4.115510e+00 9.335570e-01 1350 1 20 5.062500e+00 4.110713e+00 1.166215e+00 2700 1 30 4.500000e+00 4.104200e+00 1.414223e+00 4050 1 40 3.812500e+00 4.102669e+00 1.675121e+00 5400 1 50 4.725000e+00 4.095504e+00 1.941006e+00 6750 1 60 4.050000e+00 4.092999e+00 2.209950e+00 8100 1 70 4.606250e+00 4.091524e+00 2.472793e+00 9450 1 80 3.875000e+00 4.089694e+00 2.742083e+00 10800 1 90 3.750000e+00 4.089490e+00 3.009682e+00 12150 1 100 5.125000e+00 4.087894e+00 3.300252e+00 13500 1 110 4.500000e+00 4.087478e+00 3.584207e+00 14850 1 120 3.650000e+00 4.086704e+00 3.868269e+00 16200 1 130 4.406250e+00 4.086063e+00 4.148375e+00 17550 1 140 3.375000e+00 4.085981e+00 4.430169e+00 18900 1 150 3.000000e+00 4.085945e+00 4.721869e+00 20250 1 160 3.812500e+00 4.085838e+00 5.016029e+00 21600 1 170 4.250000e+00 4.085728e+00 5.318058e+00 22950 1 180 3.243750e+00 4.085593e+00 5.623475e+00 24300 1 190 4.306250e+00 4.085487e+00 5.929828e+00 25650 1 200 5.237500e+00 4.085446e+00 6.233061e+00 27000 1 210 4.500000e+00 4.085441e+00 6.496233e+00 28350 1 220 3.612500e+00 4.085405e+00 6.791003e+00 29700 1 230 3.700000e+00 4.085382e+00 7.111210e+00 31050 1 240 3.437500e+00 4.085254e+00 7.410425e+00 32400 1 250 4.100000e+00 4.085115e+00 7.804919e+00 33750 1 260 3.000000e+00 4.084973e+00 8.112223e+00 35100 1 270 4.918750e+00 4.084943e+00 8.418011e+00 36450 1 280 2.756250e+00 4.084920e+00 8.741799e+00 37800 1 290 3.737500e+00 4.084868e+00 9.072937e+00 39150 1 300 5.750000e+00 4.084868e+00 9.403301e+00 40500 1 310 5.156250e+00 4.084858e+00 9.732045e+00 41850 1 320 3.131250e+00 4.084855e+00 1.005091e+01 43200 1 330 4.125000e+00 4.084846e+00 1.037235e+01 44550 1 340 5.875000e+00 4.084820e+00 1.071617e+01 45900 1 350 4.587500e+00 4.084810e+00 1.104649e+01 47250 1 360 5.087500e+00 4.084805e+00 1.139588e+01 48600 1 370 4.393750e+00 4.084802e+00 1.173675e+01 49950 1 380 4.750000e+00 4.084792e+00 1.207211e+01 51300 1 390 4.437500e+00 4.084785e+00 1.239081e+01 52650 1 400 4.181250e+00 4.084785e+00 1.270015e+01 54000 1 410 3.650000e+00 4.084777e+00 1.301964e+01 55350 1 420 3.750000e+00 4.084769e+00 1.333185e+01 56700 1 430 3.725000e+00 4.084762e+00 1.364405e+01 58050 1 440 4.218750e+00 4.084751e+00 1.395445e+01 59400 1 450 5.500000e+00 4.084751e+00 1.426398e+01 60750 1 460 3.637500e+00 4.084747e+00 1.456009e+01 62100 1 470 2.993750e+00 4.084743e+00 1.486643e+01 63450 1 480 5.237500e+00 4.084743e+00 1.518675e+01 64800 1 490 4.212500e+00 4.084743e+00 1.548380e+01 66150 1 500 3.843750e+00 4.084743e+00 1.580169e+01 67500 1 510 3.425000e+00 4.084743e+00 1.609455e+01 68850 1 520 4.293750e+00 4.084743e+00 1.638239e+01 70200 1 530 2.818750e+00 4.084740e+00 1.670977e+01 71550 1 540 4.668750e+00 4.084740e+00 1.706484e+01 72900 1 550 2.750000e+00 4.084740e+00 1.750026e+01 74250 1 560 4.100000e+00 4.084740e+00 1.783084e+01 75600 1 570 3.200000e+00 4.084738e+00 1.815705e+01 76950 1 580 3.525000e+00 4.084738e+00 1.845601e+01 78300 1 590 3.125000e+00 4.084738e+00 1.876570e+01 79650 1 600 4.875000e+00 4.084736e+00 1.911208e+01 81000 1 610 4.050000e+00 4.084736e+00 1.945209e+01 82350 1 620 4.750000e+00 4.084733e+00 1.978819e+01 83700 1 627 4.875000e+00 4.084733e+00 2.003169e+01 84645 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.003169e+01 total solves : 84645 best bound : 4.084733e+00 simulation ci : 4.072209e+00 ± 6.028297e-02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.275000e+00 5.309330e+00 4.005108e-01 1350 1 20 3.031250e+00 4.739605e+00 1.077058e+00 2700 1 30 4.000000e+00 4.735300e+00 2.109749e+00 4050 1 40 3.812500e+00 4.056049e+00 3.499263e+00 5400 1 50 4.875000e+00 4.053441e+00 4.816505e+00 6750 1 60 4.000000e+00 4.049151e+00 6.406748e+00 8100 1 70 4.162500e+00 4.039926e+00 8.285488e+00 9450 1 80 4.281250e+00 4.039371e+00 1.058933e+01 10800 1 90 3.300000e+00 4.039328e+00 1.358255e+01 12150 1 100 2.862500e+00 4.039111e+00 1.659008e+01 13500 1 110 3.500000e+00 4.038056e+00 1.986615e+01 14850 1 111 4.250000e+00 4.037900e+00 2.023415e+01 14985 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.023415e+01 total solves : 14985 best bound : 4.037900e+00 simulation ci : 4.061149e+00 ± 1.441254e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_one.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 8 state variables : 1 scenarios : 1.00000e+08 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [1, 2] VariableRef in MOI.ZeroOne : [1, 1] numerical stability report matrix range [1e+00, 2e+00] objective range [5e-01, 1e+00] bounds range [1e+00, 1e+00] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.219176e+00 1.165102e+00 1.759765e+01 1680 1 20 2.078810e+00 1.166281e+00 1.915074e+01 2560 1 30 3.973033e+00 1.166907e+00 2.081989e+01 3440 1 40 3.706337e+00 1.167312e+00 3.670384e+01 5120 1 50 3.158565e+00 1.167416e+00 3.824881e+01 6000 1 60 3.642642e+00 1.167416e+00 5.390551e+01 7680 1 70 3.451253e+00 1.167416e+00 5.545429e+01 8560 1 71 2.984727e+00 1.167416e+00 5.557878e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.557878e+01 total solves : 8648 best bound : 1.167416e+00 simulation ci : 3.293853e+00 ± 1.130135e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_two.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.000000e+01 -5.809615e+01 6.265781e-01 78 1 20 -4.000000e+01 -5.809615e+01 1.344534e+00 148 1 30 -4.000000e+01 -5.809615e+01 2.167599e+00 226 1 40 -4.700000e+01 -5.809615e+01 2.999010e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.999010e+00 total solves : 296 best bound : -5.809615e+01 simulation ci : -5.346250e+01 ± 7.152725e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 9.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -6.300000e+01 -6.196125e+01 7.987881e-01 138 1 20 -4.000000e+01 -6.196125e+01 1.533747e+00 258 1 30 -7.500000e+01 -6.196125e+01 2.562774e+00 396 1 40 -4.000000e+01 -6.196125e+01 3.294878e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.294878e+00 total solves : 516 best bound : -6.196125e+01 simulation ci : -6.108750e+01 ± 7.148463e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 3.60000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -7.000000e+01 -6.546793e+01 1.294940e+00 462 1 20 -5.600000e+01 -6.546793e+01 2.072985e+00 852 1 30 -4.000000e+01 -6.546793e+01 4.373944e+00 1314 1 40 -4.000000e+01 -6.546793e+01 5.159906e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.159906e+00 total solves : 1704 best bound : -6.546793e+01 simulation ci : -5.991250e+01 ± 5.174250e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: stochastic_all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 1.200000e+01 6.389170e-01 11 1 7L 6.000000e+00 8.000000e+00 1.731443e+00 158 1 13L 6.000000e+00 8.000000e+00 2.928302e+00 224 1 18L 6.000000e+00 8.000000e+00 3.953417e+00 279 1 21L 1.200000e+01 8.000000e+00 5.188398e+00 393 1 26L 6.000000e+00 8.000000e+00 6.211407e+00 448 1 31L 1.200000e+01 8.000000e+00 7.253377e+00 503 1 36L 6.000000e+00 8.000000e+00 8.296359e+00 558 1 40L 6.000000e+00 8.000000e+00 9.102370e+00 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.102370e+00 total solves : 602 best bound : 8.000000e+00 simulation ci : 8.475000e+00 ± 8.904404e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: the_farmers_problem.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 3 scenarios : 3.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 19] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 16] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 2e+01] objective range [1e+00, 1e+03] bounds range [6e+03, 5e+05] rhs range [2e+02, 5e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -9.800000e+04 4.922260e+05 4.956729e-01 6 1 40 1.093500e+05 1.083900e+05 5.548921e-01 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.548921e-01 total solves : 240 best bound : 1.083900e+05 simulation ci : 9.772505e+04 ± 1.969816e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: vehicle_location.jl Test Summary: | Pass Fail Total Time SDDP.jl | 2457 2 2459 36m29.1s Experimental.jl | 35 35 4m10.9s Inner.jl | 25 25 4m42.8s MSPFormat.jl | 51 51 17.7s algorithm.jl | 40 40 1m18.7s binary_expansion.jl | 38 38 2.8s deterministic_equivalent.jl | 21 21 40.0s modeling_aids.jl | 47 47 17.9s user_interface.jl | 123 123 1m03.6s backward_sampling_schemes.jl | 1203 1203 6.1s bellman_functions.jl | 45 45 52.5s duality_handlers.jl | 362 362 2m10.0s forward_passes.jl | 40 40 19.1s local_improvement_search.jl | 12 12 16.5s parallel_schemes.jl | 19 19 8m19.0s risk_measures.jl | 91 91 12.3s sampling_schemes.jl | 158 158 27.6s stopping_rules.jl | 40 40 17.1s threaded.jl | 0 0.4s value_functions.jl | 28 28 23.6s visualization.jl | 9 2 11 1m24.5s test_PublicationPlot | 5 5 19.8s test_PublicationPlot_different_lengths | 1 1 0.9s test_SpaghettiPlot | 3 2 5 28.8s FAST_hydro_thermal.jl | 3 3 15.7s FAST_production_management.jl | 2 2 4.5s FAST_quickstart.jl | 2 2 1.8s Hydro_thermal.jl | 0 19.7s StochDynamicProgramming.jl_multistock.jl | 3 3 15.5s StochDynamicProgramming.jl_stock.jl | 3 3 5.5s StructDualDynProg.jl_prob5.2_2stages.jl | 1 1 4.5s StructDualDynProg.jl_prob5.2_3stages.jl | 2 2 2.9s agriculture_mccardle_farm.jl | 2 2 15.6s air_conditioning.jl | 6 6 9.4s air_conditioning_forward.jl | 2 2 2.7s all_blacks.jl | 1 1 2.5s asset_management_simple.jl | 1 1 5.4s asset_management_stagewise.jl | 2 2 4.4s belief.jl | 1 1 21.2s biobjective_hydro.jl | 10 10 8.3s booking_management.jl | 2 2 32.0s generation_expansion.jl | 2 2 3m02.7s hydro_valley.jl | 9 9 10.8s infinite_horizon_hydro_thermal.jl | 4 4 8.0s infinite_horizon_trivial.jl | 1 1 1.5s inner_hydro_1d.jl | 1 1 9.6s no_strong_duality.jl | 1 1 1.5s objective_state_newsvendor.jl | 4 4 51.4s sldp_example_one.jl | 1 1 1m11.1s sldp_example_two.jl | 3 3 16.2s stochastic_all_blacks.jl | 1 1 13.2s the_farmers_problem.jl | 0 6.2s vehicle_location.jl | 0 0.2s RNG of the outermost testset: Xoshiro(0xc9c6631cab705ceb, 0x401d7a721aee9637, 0x9b02d1e1294a9a10, 0x40176ede8018c25b, 0x51d0f3ee4b5e725d) ERROR: LoadError: Some tests did not pass: 2457 passed, 2 failed, 0 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/SDDP/39RYL/test/runtests.jl:24 Testing failed after 2179.08s ERROR: LoadError: Package SDDP errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2674 [3] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2523 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:548 [5] kwcall(::@NamedTuple{julia_args::Cmd, io::IOContext{IO}}, ::typeof(Pkg.API.test), ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:525 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:172 [7] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:161 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:160 [9] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:160 [inlined] [10] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkg::String) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:159 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:219 [12] include(mod::Module, _path::String) @ Base ./Base.jl:309 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [14] _start() @ Base ./client.jl:577 in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 PkgEval failed after 2291.16s: package has test failures