Package evaluation to test SDDP on Julia 1.14.0-DEV.1840 (ab7ba34e40*) started at 2026-03-03T19:33:39.998 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 13.79s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [f4570300] + SDDP v1.13.1 Updating `~/.julia/environments/v1.14/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.3 [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 v2.5.1 [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 v1.3.2 [cd3eb016] + HTTP v1.10.19 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.4.0 [4076af6c] + JuMP v1.29.4 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.49.0 [739be429] + MbedTLS v1.1.10 [d8a4904e] + MutableArithmetics v1.6.7 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.6.1 [bac558e1] + OrderedCollections v1.8.1 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.2 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.13.1 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.7.1 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [ec057cc2] + StructUtils v2.6.3 [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 v2.28.1010+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 v1.13.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown 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 v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [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 v2025.12.2 [4536629a] + OpenBLAS_jll v0.3.30+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.5+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [8e850b90] + libblastrampoline_jll v5.15.0+0 Installation completed after 5.64s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 27816.5 ms ✓ SDDP 1 dependency successfully precompiled in 30 seconds. 210 already precompiled. Precompilation completed after 55.86s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_x8fhpb/Project.toml` [87dc4568] HiGHS v1.21.1 [b6b21f68] Ipopt v1.14.1 [682c06a0] JSON v1.4.0 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.6 [f4570300] SDDP v1.13.1 [10745b16] Statistics v1.11.1 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [44cfe95a] Pkg v1.14.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_x8fhpb/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [6e4b80f9] BenchmarkTools v1.6.3 [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 v2.5.1 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.3 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Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. 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: 0.41 plus 11.92 for vertex selection. Node: 2 - elapsed time: 0.31 plus 0.29 for vertex selection. Node: 1 - elapsed time: 0.3 plus 0.29 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 13.518027658 ┌ Warning: You must select an optimizer for performing vertex selection. └ @ SDDP.Inner ~/.julia/packages/SDDP/ScjyB/src/Inner.jl:1048 Node: 19 - elapsed time: 0.37 plus 0.34 for vertex selection. Node: 18 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 17 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 16 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 15 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 14 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 13 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 12 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 11 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 10 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 9 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 8 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 7 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 6 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 5 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 4 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 3 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 2 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 1 - elapsed time: 0.49 plus 0.33 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/ScjyB/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 6.047139e-01 4 1 3 0.000000e+00 0.000000e+00 1.596239e+00 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.596239e+00 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.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 5.467718e-01 9 1 20 7.500000e+04 1.075000e+05 1.303598e+00 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.303598e+00 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/ScjyB/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/ScjyB/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/ScjyB/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 2.175382e+00 12 1 10 2.500000e+00 3.361111e+01 2.205578e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.205578e+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 5.878551e-01 12 1 10 2.500000e+00 3.361111e+01 6.215341e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.215341e-01 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 1.119208e-02 46 1 50 0.000000e+00 1.191663e+02 6.663351e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.663351e-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 1.156211e-02 46 1 50 0.000000e+00 1.191663e+02 5.426080e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.426080e-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.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 3.863645e+00 103 1 3S -5.785826e+01 -6.755367e+01 5.590676e+00 309 1 4S -6.230988e+01 -6.688020e+01 6.640111e+00 412 1 5S -7.577792e+01 -6.680771e+01 7.810239e+00 515 1 6S -6.064080e+01 -6.678327e+01 8.970803e+00 618 1 13S -3.268889e+01 -6.677644e+01 1.463558e+01 1339 1 23S -3.268889e+01 -6.677644e+01 2.055225e+01 2369 1 33S -8.368889e+01 -6.677644e+01 2.650585e+01 3399 1 43S -8.368889e+01 -6.677644e+01 3.228856e+01 4429 1 53S -4.868889e+01 -6.677644e+01 3.821751e+01 5459 1 63S -8.068889e+01 -6.677644e+01 4.412071e+01 6489 1 73S -7.168889e+01 -6.677644e+01 5.002401e+01 7519 1 83S -7.168889e+01 -6.677644e+01 5.606228e+01 8549 1 93S -6.068889e+01 -6.677644e+01 6.175714e+01 9579 1 100 -8.368889e+01 -6.677644e+01 6.494596e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.494596e+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 6.990194e-03 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.990194e-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/ScjyB/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} : [1, 1] 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 9.000000e+00 6.000000e+00 3.227531e+02 2 5 20 7.000000e+00 6.000000e+00 3.279300e+02 40 5 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.279300e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 5.600000e+00 ± 9.037950e-01 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/ScjyB/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 5.975480e-01 48 1 20 9.000000e+00 6.000000e+00 1.061149e+00 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.061149e+00 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/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/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 4.276068e-01 4 1 50 0.000000e+00 0.000000e+00 7.595220e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 7.595220e-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/ScjyB/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/ScjyB/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/ScjyB/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/ScjyB/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/v1.14/Test/src/Test.jl:781 [inlined] [2] test_SpaghettiPlot() @ Main.TestVisualization ~/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:49 [3] macro expansion @ ~/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:17 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2243 [inlined] [5] runtests() @ Main.TestVisualization ~/.julia/packages/SDDP/ScjyB/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/ScjyB/test/visualization/visualization.jl:51 test_SpaghettiPlot: Test Failed at /home/pkgeval/.julia/packages/SDDP/ScjyB/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/v1.14/Test/src/Test.jl:781 [inlined] [2] test_SpaghettiPlot() @ Main.TestVisualization ~/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:55 [3] macro expansion @ ~/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:17 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2243 [inlined] [5] runtests() @ Main.TestVisualization ~/.julia/packages/SDDP/ScjyB/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 7.461423e+00 5 1 20 0.000000e+00 -1.000000e+01 8.130694e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.130694e+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.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 8.139408e-01 52 1 10 -2.396000e+01 -2.396000e+01 8.229978e-01 92 1 15 -4.260000e+01 -2.396000e+01 8.335049e-01 132 1 20 -2.396000e+01 -2.396000e+01 8.448069e-01 172 1 25 -5.320000e+00 -2.396000e+01 8.604479e-01 224 1 30 -5.320000e+00 -2.396000e+01 8.753378e-01 264 1 35 -2.396000e+01 -2.396000e+01 8.910179e-01 304 1 40 -2.396000e+01 -2.396000e+01 9.085448e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.085448e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 1.24s / 71.6% 12.0MiB / 61.2% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 625ms 70.2% 15.6ms 1.58MiB 21.5% 40.4KiB solve_subproblem 120 623ms 70.0% 5.19ms 1.41MiB 19.2% 12.0KiB get_dual_solution 120 57.8μs 0.0% 481ns 13.1KiB 0.2% 112B sample_scenario 40 545μs 0.1% 13.6μs 22.3KiB 0.3% 572B backward_pass 40 254ms 28.5% 6.34ms 5.58MiB 75.9% 143KiB solve_subproblem 160 27.9ms 3.1% 174μs 771KiB 10.2% 4.82KiB get_dual_solution 160 1.43ms 0.2% 8.96μs 205KiB 2.7% 1.28KiB prepare_backward_pass 160 115μs 0.0% 720ns 15.0KiB 0.2% 96.0B calculate_bound 40 11.1ms 1.3% 278μs 189KiB 2.5% 4.73KiB get_dual_solution 40 26.4μs 0.0% 660ns 4.38KiB 0.1% 112B get_dual_solution 36 12.9μs 0.0% 357ns 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.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 5.554950e-01 52 1 10 -2.396000e+01 -2.396000e+01 5.666451e-01 92 1 15 -2.396000e+01 -2.396000e+01 5.806270e-01 132 1 20 -4.260000e+01 -2.396000e+01 5.976350e-01 172 1 25 -5.320000e+00 -2.396000e+01 6.192901e-01 224 1 30 -2.396000e+01 -2.396000e+01 6.426351e-01 264 1 35 -2.396000e+01 -2.396000e+01 6.690140e-01 304 1 40 -5.320000e+00 -2.396000e+01 6.982920e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.982920e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 707ms / 95.4% 13.9MiB / 94.4% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 380ms 56.4% 9.50ms 1.58MiB 12.0% 40.4KiB solve_subproblem 120 377ms 55.9% 3.14ms 1.41MiB 10.7% 12.0KiB get_dual_solution 120 51.3μs 0.0% 428ns 13.1KiB 0.1% 112B sample_scenario 40 662μs 0.1% 16.5μs 22.5KiB 0.2% 575B backward_pass 40 280ms 41.5% 7.00ms 11.4MiB 86.5% 291KiB solve_subproblem 160 29.9ms 4.4% 187μs 772KiB 5.7% 4.83KiB get_dual_solution 160 1.64ms 0.2% 10.3μs 205KiB 1.5% 1.28KiB prepare_backward_pass 160 184μs 0.0% 1.15μs 15.0KiB 0.1% 96.0B calculate_bound 40 14.1ms 2.1% 352μs 190KiB 1.4% 4.76KiB get_dual_solution 40 19.0μs 0.0% 474ns 4.38KiB 0.0% 112B get_dual_solution 36 11.9μs 0.0% 330ns 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 4.045990e-01 5 1 2 -2.500000e+00 -2.000000e+00 5.631559e-01 14 1 3 -1.000000e+00 -2.000000e+00 5.642331e-01 19 1 4 -1.000000e+00 -2.000000e+00 5.651150e-01 24 1 5 -1.000000e+00 -2.000000e+00 5.723550e-01 29 1 6 -3.000000e+00 -2.000000e+00 5.733631e-01 34 1 7 -1.000000e+00 -2.000000e+00 5.741699e-01 39 1 8 -1.000000e+00 -2.000000e+00 5.749500e-01 44 1 9 -3.000000e+00 -2.000000e+00 5.758259e-01 49 1 10 -1.000000e+00 -2.000000e+00 5.766740e-01 54 1 11 -3.000000e+00 -2.000000e+00 5.775409e-01 59 1 12 -3.000000e+00 -2.000000e+00 5.783830e-01 64 1 13 -1.000000e+00 -2.000000e+00 5.795619e-01 69 1 14 -1.000000e+00 -2.000000e+00 5.804529e-01 74 1 15 -3.000000e+00 -2.000000e+00 5.816820e-01 79 1 16 -1.000000e+00 -2.000000e+00 5.827899e-01 84 1 17 -3.000000e+00 -2.000000e+00 5.840161e-01 89 1 18 -3.000000e+00 -2.000000e+00 5.854049e-01 94 1 19 -1.000000e+00 -2.000000e+00 5.867300e-01 99 1 20 -3.000000e+00 -2.000000e+00 5.879209e-01 104 1 21 -1.000000e+00 -2.000000e+00 9.698651e-01 113 1 22 -1.000000e+00 -2.000000e+00 9.712040e-01 118 1 23 -3.000000e+00 -2.000000e+00 9.724109e-01 123 1 24 -3.000000e+00 -2.000000e+00 9.872680e-01 128 1 25 -1.000000e+00 -2.000000e+00 9.885950e-01 133 1 26 -3.000000e+00 -2.000000e+00 9.906530e-01 138 1 27 -3.000000e+00 -2.000000e+00 9.919379e-01 143 1 28 -1.000000e+00 -2.000000e+00 9.932020e-01 148 1 29 -3.000000e+00 -2.000000e+00 9.945221e-01 153 1 30 -3.000000e+00 -2.000000e+00 9.958639e-01 158 1 31 -1.000000e+00 -2.000000e+00 9.971850e-01 163 1 32 -1.000000e+00 -2.000000e+00 9.984550e-01 168 1 33 -1.000000e+00 -2.000000e+00 9.997439e-01 173 1 34 -3.000000e+00 -2.000000e+00 1.001100e+00 178 1 35 -1.000000e+00 -2.000000e+00 1.002389e+00 183 1 36 -3.000000e+00 -2.000000e+00 1.003667e+00 188 1 37 -1.000000e+00 -2.000000e+00 1.005038e+00 193 1 38 -1.000000e+00 -2.000000e+00 1.006378e+00 198 1 39 -1.000000e+00 -2.000000e+00 1.007870e+00 203 1 40 -1.000000e+00 -2.000000e+00 1.009325e+00 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.009325e+00 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 1.088577e+00 51 1 24 2.178733e+02 2.251256e+02 2.158008e+00 3972 1 30 2.138334e+03 2.336430e+02 3.633378e+00 7674 1 38 8.025312e+02 2.352957e+02 4.926777e+00 10194 1 46 1.737622e+02 2.358930e+02 6.014079e+00 12054 1 56 1.051492e+02 2.360772e+02 7.062383e+00 13608 1 63 1.493193e+03 2.362190e+02 8.740060e+00 15909 1 71 1.519535e+02 2.362929e+02 9.763336e+00 17205 1 98 5.715017e+02 2.364082e+02 1.510946e+01 23094 1 100 4.969839e+02 2.364135e+02 1.599428e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.599428e+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.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 1.966645e+00 1400 1 20 -4.764789e+00 -4.394789e+00 2.268950e+00 2800 1 30 -4.672487e+00 -4.377000e+00 2.578709e+00 4200 1 40 -4.483495e+00 -4.370632e+00 2.892673e+00 5600 1 50 -4.167321e+00 -4.364999e+00 3.221657e+00 7000 1 60 -4.362455e+00 -4.358864e+00 3.556040e+00 8400 1 70 -4.849916e+00 -4.355337e+00 3.887368e+00 9800 1 80 -4.861568e+00 -4.353006e+00 4.235780e+00 11200 1 90 -4.268264e+00 -4.350407e+00 4.587824e+00 12600 1 100 -4.539897e+00 -4.348641e+00 4.942263e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.942263e+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.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 1.833723e+00 1050 1 20 -1.529197e+00 -1.471817e+00 1.922367e+00 1600 1 30 -1.410768e+00 -1.471408e+00 2.117298e+00 2650 1 40 -1.596461e+00 -1.471258e+00 2.212820e+00 3200 1 50 -1.002277e+00 -1.471216e+00 2.408139e+00 4250 1 60 -1.085156e+00 -1.471164e+00 2.510915e+00 4800 1 70 -1.391746e+00 -1.471164e+00 2.716736e+00 5850 1 80 -1.448703e+00 -1.471132e+00 2.821924e+00 6400 1 90 -1.488989e+00 -1.471087e+00 3.026504e+00 7450 1 100 -1.564260e+00 -1.471075e+00 3.141919e+00 8000 1 110 -1.738157e+00 -1.471075e+00 3.253190e+00 8550 1 120 -1.591292e+00 -1.471075e+00 3.373568e+00 9100 1 130 -1.271481e+00 -1.471075e+00 3.486238e+00 9650 1 140 -1.249746e+00 -1.471075e+00 3.611517e+00 10200 1 150 -1.536222e+00 -1.471075e+00 3.740009e+00 10750 1 160 -1.565422e+00 -1.471075e+00 3.881204e+00 11300 1 170 -1.631076e+00 -1.471075e+00 4.019248e+00 11850 1 180 -1.494909e+00 -1.471075e+00 4.154319e+00 12400 1 182 -9.083563e-01 -1.471075e+00 4.178940e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.178940e+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.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 5.497959e-01 54 1 20 3.336455e+05 3.402383e+05 5.627990e-01 104 1 30 3.993519e+05 3.403155e+05 5.764380e-01 158 1 40 3.337559e+05 3.403155e+05 5.887349e-01 208 1 48 3.337559e+05 3.403155e+05 6.017499e-01 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.017499e-01 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 7.109020e-01 92 1 20 4.506600e+05 4.054833e+05 7.340760e-01 172 1 30 3.959476e+05 4.067125e+05 7.565620e-01 264 1 40 4.497721e+05 4.067125e+05 7.802849e-01 344 1 47 3.959476e+05 4.067125e+05 8.017149e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.017149e-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 9.520443e+00 14 1 40 2.308500e+03 4.074139e+03 1.048784e+01 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.048784e+01 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.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 3.407484e+00 8 1 5L 4.000000e+04 6.250000e+04 4.529332e+00 52 1 11L 4.000000e+04 6.250000e+04 5.591357e+00 100 1 17L 4.000000e+04 6.250000e+04 6.690396e+00 148 1 20L 6.000000e+04 6.250000e+04 7.331919e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.331919e+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.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 5.107191e-01 8 1 15 5.500000e+04 6.250000e+04 1.554604e+00 132 1 20 4.000000e+04 6.250000e+04 1.911535e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.911535e+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 1.508494e+00 5 1 10 4.000000e+04 6.250000e+04 2.046908e+00 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.046908e+00 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 9.607670e-01 6 1 20L 9.000000e+00 9.000000e+00 1.098988e+00 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.098988e+00 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 2.477057e+00 87 1 10 -1.109375e+01 2.605769e-01 2.490111e+00 142 1 15 3.105797e+00 5.434132e-01 2.504039e+00 197 1 20 -2.463349e+01 1.503415e+00 2.518684e+00 252 1 25 -1.421085e-14 1.514085e+00 2.533808e+00 307 1 30 4.864000e+01 1.514085e+00 5.053790e+00 394 1 35 4.864000e+01 1.514085e+00 5.070089e+00 449 1 40 -8.870299e+00 1.514085e+00 5.088845e+00 504 1 45 -1.428571e+00 1.514085e+00 5.107683e+00 559 1 48 -1.428571e+00 1.514085e+00 5.120545e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.120545e+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.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 2.807455e+00 278 1 20 1.440356e+01 1.278425e+00 2.851616e+00 428 1 30 8.388546e+00 1.278425e+00 2.922148e+00 706 1 40 6.666667e-03 1.278410e+00 2.966214e+00 856 1 50 -5.614035e+00 1.278410e+00 3.042860e+00 1134 1 60 1.426676e+01 1.278410e+00 3.097264e+00 1284 1 64 1.261296e+01 1.278410e+00 3.120103e+00 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.120103e+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.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 1.611162e+00 278 1 20 1.111084e+01 1.278410e+00 1.678330e+00 428 1 30 2.293779e+01 1.278410e+00 1.781098e+00 706 1 40 1.426676e+01 1.278410e+00 1.886359e+00 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.886359e+00 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 7.388259e+00 900 1 20 6.374753e+00 1.361934e+01 7.743572e+00 1720 1 30 2.848217e+01 1.624016e+01 8.590668e+00 3036 1 40 1.973944e+01 1.776547e+01 9.667743e+00 4192 1 50 4.000000e+00 1.889360e+01 1.051811e+01 5020 1 60 1.142478e+01 1.907862e+01 1.147490e+01 5808 1 70 9.386421e+00 1.961295e+01 1.239840e+01 6540 1 80 5.667851e+01 1.890911e+01 1.312967e+01 7088 1 90 3.740597e+01 1.993139e+01 1.469121e+01 8180 1 100 9.867183e+00 2.001688e+01 1.544624e+01 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.544624e+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 4.249497e+00 36 1 10 0.000000e+00 0.000000e+00 4.294644e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.294644e+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 6.707907e-03 407 1 10 2.850000e+02 5.728212e+02 6.755710e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.755710e-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 6.867886e-03 778 1 10 2.825000e+02 3.465177e+02 6.875181e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.875181e-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 6.989002e-03 1149 1 10 2.587500e+02 2.052799e+02 7.082105e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.082105e-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 7.769108e-03 1520 1 10 2.875000e+02 4.661908e+02 7.871509e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.871509e-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 8.316994e-03 1891 1 10 1.000000e+02 1.129771e+02 7.035804e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.035804e-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 7.694960e-03 2262 1 10 1.625000e+02 2.794553e+02 7.260394e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.260394e-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 8.262157e-03 2633 1 10 5.487500e+02 4.077574e+02 8.210802e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.210802e-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 9.421110e-03 3004 1 10 6.771875e+02 5.210100e+02 8.529401e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.529401e-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 8.579016e-03 3375 1 10 5.312500e+01 5.938345e+01 7.525301e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.525301e-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.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 2.712214e+00 235 1 10 1.000000e+01 9.159200e+00 3.203134e+00 310 1 15 1.000000e+01 9.159200e+00 3.746079e+00 385 1 20 1.000000e+01 9.159200e+00 4.260185e+00 460 1 25 1.000000e+01 9.159200e+00 7.080151e+00 695 1 30 4.000000e+00 9.159200e+00 7.574761e+00 770 1 35 1.000000e+01 9.159200e+00 8.060658e+00 845 1 40 1.000000e+01 9.159200e+00 8.598116e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.598116e+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.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 1.770853e+00 510 1 20 1.000000e+01 6.834387e+00 3.467450e+00 720 1 30 7.000000e+00 6.834387e+00 7.495948e+00 1230 1 40 1.000000e+01 6.823805e+00 9.195403e+00 1440 1 50 3.000000e+00 6.823805e+00 1.338035e+01 1950 1 60 2.000000e+00 6.823805e+00 1.510181e+01 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.510181e+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.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 1.195381e+01 920 1 20 6.049875e+06 2.075240e+06 1.448533e+01 1340 1 30 5.496647e+05 2.078257e+06 2.457478e+01 2260 1 40 3.985383e+04 2.078257e+06 2.704049e+01 2680 1 50 2.994548e+05 2.078257e+06 3.706052e+01 3600 1 60 3.799457e+06 2.078257e+06 3.962885e+01 4020 1 61 3.549665e+06 2.078257e+06 3.987568e+01 4062 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.987568e+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.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 3.004213e+01 920 1 20L 2.799668e+06 2.079457e+06 4.913113e+01 1340 1 30L 3.799443e+06 2.079457e+06 7.729220e+01 2260 1 40L 4.299882e+06 2.079457e+06 9.681811e+01 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.681811e+01 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.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 3.316782e+00 1914 1 200 0.000000e+00 1.191645e+02 3.734702e+00 3840 1 300 7.500000e+01 1.191666e+02 4.213613e+00 5738 1 328 2.500000e+00 1.191667e+02 4.332240e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.332240e+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.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 8.859231e-01 2806 1 200 0.000000e+00 1.191666e+02 1.519768e+00 4749 1 287 5.000000e+00 1.191667e+02 2.015840e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.015840e+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 4.133780e-01 1033 1 20 8.000000e+00 2.000000e+01 4.415150e-01 1209 1 30 1.200000e+01 2.000000e+01 5.825360e-01 2304 1 40 3.000000e+01 2.000000e+01 6.931770e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.931770e-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 9.701281e-01 35 1 10 7.500000e+02 2.935390e+03 1.033285e+00 350 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.033285e+00 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: 0.35 plus 0.55 for vertex selection. Node: 2 - elapsed time: 0.3 plus 0.19 for vertex selection. Node: 1 - elapsed time: 0.3 plus 0.16 for vertex selection. First-stage upper bound: 2969.680973503913 Total time for upper bound: 1.847370861 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 1.770849e-01 3 1 40 2.000000e+00 2.000000e+00 3.715880e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.715880e-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.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 1.801427e+00 1350 1 20 5.062500e+00 4.110713e+00 2.017348e+00 2700 1 30 4.500000e+00 4.104200e+00 2.257104e+00 4050 1 40 3.812500e+00 4.102669e+00 2.502017e+00 5400 1 50 4.725000e+00 4.095504e+00 2.761573e+00 6750 1 60 4.050000e+00 4.092999e+00 2.998295e+00 8100 1 70 4.606250e+00 4.091524e+00 3.631900e+00 9450 1 80 3.875000e+00 4.089694e+00 3.887407e+00 10800 1 90 3.750000e+00 4.089490e+00 4.134660e+00 12150 1 100 5.125000e+00 4.087894e+00 4.404980e+00 13500 1 110 4.500000e+00 4.087478e+00 4.662768e+00 14850 1 120 3.650000e+00 4.086704e+00 4.945313e+00 16200 1 130 4.406250e+00 4.086063e+00 5.217983e+00 17550 1 140 3.375000e+00 4.085981e+00 5.486850e+00 18900 1 150 3.000000e+00 4.085945e+00 5.760218e+00 20250 1 160 3.812500e+00 4.085838e+00 6.036667e+00 21600 1 170 4.250000e+00 4.085728e+00 6.313100e+00 22950 1 180 3.243750e+00 4.085593e+00 6.610540e+00 24300 1 190 4.306250e+00 4.085487e+00 6.889072e+00 25650 1 200 5.237500e+00 4.085446e+00 7.200847e+00 27000 1 210 4.500000e+00 4.085441e+00 7.498722e+00 28350 1 220 3.612500e+00 4.085405e+00 7.794209e+00 29700 1 230 3.700000e+00 4.085382e+00 8.123227e+00 31050 1 240 3.437500e+00 4.085254e+00 8.455506e+00 32400 1 250 4.100000e+00 4.085115e+00 8.804487e+00 33750 1 260 3.000000e+00 4.084973e+00 9.134523e+00 35100 1 270 4.918750e+00 4.084943e+00 9.473262e+00 36450 1 280 2.756250e+00 4.084920e+00 9.836182e+00 37800 1 290 3.737500e+00 4.084868e+00 1.020458e+01 39150 1 300 5.750000e+00 4.084868e+00 1.055625e+01 40500 1 310 5.156250e+00 4.084858e+00 1.088626e+01 41850 1 320 3.131250e+00 4.084855e+00 1.118455e+01 43200 1 330 4.125000e+00 4.084846e+00 1.145531e+01 44550 1 340 5.875000e+00 4.084820e+00 1.195217e+01 45900 1 350 4.587500e+00 4.084810e+00 1.227146e+01 47250 1 360 5.087500e+00 4.084805e+00 1.262449e+01 48600 1 370 4.393750e+00 4.084802e+00 1.295474e+01 49950 1 380 4.750000e+00 4.084792e+00 1.329443e+01 51300 1 390 4.437500e+00 4.084785e+00 1.361591e+01 52650 1 400 4.181250e+00 4.084785e+00 1.393283e+01 54000 1 410 3.650000e+00 4.084777e+00 1.427604e+01 55350 1 420 3.750000e+00 4.084769e+00 1.462800e+01 56700 1 430 3.725000e+00 4.084762e+00 1.496804e+01 58050 1 440 4.218750e+00 4.084751e+00 1.531451e+01 59400 1 450 5.500000e+00 4.084751e+00 1.569595e+01 60750 1 460 3.637500e+00 4.084747e+00 1.606913e+01 62100 1 470 2.993750e+00 4.084743e+00 1.643377e+01 63450 1 480 5.237500e+00 4.084743e+00 1.681715e+01 64800 1 490 4.212500e+00 4.084743e+00 1.718766e+01 66150 1 500 3.843750e+00 4.084743e+00 1.755973e+01 67500 1 510 3.425000e+00 4.084743e+00 1.793953e+01 68850 1 520 4.293750e+00 4.084743e+00 1.828021e+01 70200 1 530 2.818750e+00 4.084740e+00 1.864633e+01 71550 1 540 4.668750e+00 4.084740e+00 1.900155e+01 72900 1 550 2.750000e+00 4.084740e+00 1.935214e+01 74250 1 560 4.100000e+00 4.084740e+00 1.965469e+01 75600 1 570 3.200000e+00 4.084738e+00 1.998660e+01 76950 1 571 4.600000e+00 4.084738e+00 2.002334e+01 77085 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.002334e+01 total solves : 77085 best bound : 4.084738e+00 simulation ci : 4.070107e+00 ± 6.327749e-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.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 4.375000e+00 5.745035e+00 1.145499e+00 1350 1 20 4.125000e+00 5.603135e+00 1.994105e+00 2700 1 30 3.600000e+00 5.602389e+00 3.209875e+00 4050 1 40 4.900000e+00 4.400319e+00 4.473460e+00 5400 1 50 4.375000e+00 4.336718e+00 5.969380e+00 6750 1 60 3.437500e+00 4.046159e+00 7.580973e+00 8100 1 70 3.050000e+00 4.044965e+00 9.457168e+00 9450 1 80 4.018750e+00 4.044865e+00 1.180159e+01 10800 1 90 3.500000e+00 4.043133e+00 1.445192e+01 12150 1 100 3.525000e+00 4.039652e+00 1.750588e+01 13500 1 109 3.375000e+00 4.039550e+00 2.031046e+01 14715 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.031046e+01 total solves : 14715 best bound : 4.039550e+00 simulation ci : 4.019548e+00 ± 1.439142e-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.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 1.905269e+01 1680 1 20 2.078810e+00 1.166281e+00 2.054562e+01 2560 1 30 3.973033e+00 1.166907e+00 2.221779e+01 3440 1 40 3.706337e+00 1.167312e+00 3.775844e+01 5120 1 50 3.158565e+00 1.167416e+00 3.933435e+01 6000 1 60 3.642642e+00 1.167416e+00 5.482376e+01 7680 1 70 3.451253e+00 1.167416e+00 5.638388e+01 8560 1 71 2.984727e+00 1.167416e+00 5.650815e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.650815e+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.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 1.102785e+00 78 1 20 -4.000000e+01 -5.809615e+01 1.819541e+00 148 1 30 -4.000000e+01 -5.809615e+01 2.627783e+00 226 1 40 -4.700000e+01 -5.809615e+01 3.376753e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.376753e+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.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 1.117631e+00 138 1 20 -4.000000e+01 -6.196125e+01 1.846554e+00 258 1 30 -7.500000e+01 -6.196125e+01 2.782657e+00 396 1 40 -4.000000e+01 -6.196125e+01 3.485643e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.485643e+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.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 1.701222e+00 462 1 20 -5.600000e+01 -6.546793e+01 2.459169e+00 852 1 30 -4.000000e+01 -6.546793e+01 4.560190e+00 1314 1 40 -4.000000e+01 -6.546793e+01 5.317206e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.317206e+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.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 1.366667e+01 1.506916e+00 11 1 7L 6.000000e+00 8.000000e+00 2.576923e+00 158 1 12L 6.000000e+00 8.000000e+00 3.672510e+00 213 1 17L 6.000000e+00 8.000000e+00 4.736896e+00 268 1 21L 1.200000e+01 8.000000e+00 6.218964e+00 393 1 27L 6.000000e+00 8.000000e+00 7.423039e+00 459 1 32L 1.200000e+01 8.000000e+00 8.492917e+00 514 1 37L 6.000000e+00 8.000000e+00 9.626432e+00 569 1 40L 6.000000e+00 8.000000e+00 1.027447e+01 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.027447e+01 total solves : 602 best bound : 8.000000e+00 simulation ci : 8.400000e+00 ± 9.462496e-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 1.046873e+00 6 1 40 1.093500e+05 1.083900e+05 1.101598e+00 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.101598e+00 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 | 2453 2 2455 40m12.5s Experimental.jl | 35 35 4m38.9s Inner.jl | 25 25 5m35.0s MSPFormat.jl | 51 51 23.2s algorithm.jl | 40 40 1m29.8s binary_expansion.jl | 38 38 4.6s deterministic_equivalent.jl | 21 21 40.0s modeling_aids.jl | 47 47 24.3s user_interface.jl | 119 119 1m17.5s backward_sampling_schemes.jl | 1203 1203 7.1s bellman_functions.jl | 45 45 1m00.8s duality_handlers.jl | 362 362 3m15.1s forward_passes.jl | 40 40 25.0s local_improvement_search.jl | 12 12 24.1s parallel_schemes.jl | 19 19 8m36.3s risk_measures.jl | 91 91 17.0s sampling_schemes.jl | 158 158 23.9s stopping_rules.jl | 40 40 17.5s threaded.jl | 0 0.4s value_functions.jl | 28 28 29.6s visualization.jl | 9 2 11 1m09.9s test_PublicationPlot | 5 5 19.8s test_PublicationPlot_different_lengths | 1 1 1.0s test_SpaghettiPlot | 3 2 5 9.3s FAST_hydro_thermal.jl | 3 3 14.0s FAST_production_management.jl | 2 2 6.2s FAST_quickstart.jl | 2 2 2.8s Hydro_thermal.jl | 0 21.8s StochDynamicProgramming.jl_multistock.jl | 3 3 16.3s StochDynamicProgramming.jl_stock.jl | 3 3 6.7s StructDualDynProg.jl_prob5.2_2stages.jl | 1 1 4.9s StructDualDynProg.jl_prob5.2_3stages.jl | 2 2 3.6s agriculture_mccardle_farm.jl | 2 2 17.6s air_conditioning.jl | 6 6 12.0s air_conditioning_forward.jl | 2 2 3.7s all_blacks.jl | 1 1 2.6s asset_management_simple.jl | 1 1 6.8s asset_management_stagewise.jl | 2 2 7.7s belief.jl | 1 1 20.5s biobjective_hydro.jl | 10 10 9.0s booking_management.jl | 2 2 32.3s generation_expansion.jl | 2 2 2m34.9s hydro_valley.jl | 9 9 23.2s infinite_horizon_hydro_thermal.jl | 4 4 10.1s infinite_horizon_trivial.jl | 1 1 1.6s inner_hydro_1d.jl | 1 1 11.3s no_strong_duality.jl | 1 1 1.7s objective_state_newsvendor.jl | 4 4 50.9s sldp_example_one.jl | 1 1 1m11.8s sldp_example_two.jl | 3 3 16.5s stochastic_all_blacks.jl | 1 1 14.2s the_farmers_problem.jl | 0 6.4s vehicle_location.jl | 0 0.1s RNG of the outermost testset: Xoshiro(0x985cc1e0a789804b, 0x332e50624b1ff9aa, 0x5401b8d099bd8f1e, 0xfabe2ad4f7034030, 0xb1237aed4ab3fa2f) ERROR: LoadError: Some tests did not pass: 2453 passed, 2 failed, 0 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/SDDP/ScjyB/test/runtests.jl:24 Testing failed after 2423.97s ERROR: LoadError: Package SDDP errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.14/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/v1.14/Pkg/src/Operations.jl:3138 [3] test @ /opt/julia/share/julia/stdlib/v1.14/Pkg/src/Operations.jl:3003 [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/v1.14/Pkg/src/API.jl:586 [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/v1.14/Pkg/src/API.jl:562 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/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/v1.14/Pkg/src/API.jl:161 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.14/Pkg/src/API.jl:160 [9] test @ /opt/julia/share/julia/stdlib/v1.14/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/v1.14/Pkg/src/API.jl:159 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:223 [12] include(mod::Module, _path::String) @ Base ./Base.jl:323 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:344 [14] _start() @ Base ./client.jl:585 in expression starting at /PkgEval.jl/scripts/evaluate.jl:214 PkgEval failed after 2525.23s: package has test failures