Package evaluation to test SDDP on Julia 1.14.0-DEV.1711 (41ad7d9eeb*) started at 2026-02-12T19:00:06.307 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 12.48s ################################################################################ # 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 v2.5.0 [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 v1.1.9 [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 v1.5.1 [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 v2.6.2 [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 v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.15.0+0 Installation completed after 5.47s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling packages... 28919.3 ms ✓ SDDP 108711.3 ms ✓ Plots 2 dependencies successfully precompiled in 141 seconds. 209 already precompiled. Precompilation completed after 163.81s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_1Vl6iU/Project.toml` [87dc4568] HiGHS v1.21.1 [b6b21f68] Ipopt v1.14.0 [682c06a0] JSON v1.4.0 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.5 [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_1Vl6iU/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 v2.5.0 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.3 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Testing Running tests... [ Info: Experimental.jl [ Info: fetching remote ref https://jump.dev/MathOptFormat/schemas/mof.1.schema.json [ Info: Inner.jl Node: 3 - elapsed time: 0.4 plus 10.36 for vertex selection. Node: 2 - elapsed time: 0.32 plus 0.3 for vertex selection. Node: 1 - elapsed time: 0.32 plus 0.3 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 12.003551457999999 ┌ 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 0.36 for vertex selection. Node: 18 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 17 - elapsed time: 0.46 plus 0.33 for vertex selection. Node: 16 - elapsed time: 0.45 plus 0.33 for vertex selection. Node: 15 - elapsed time: 0.46 plus 0.34 for vertex selection. Node: 14 - elapsed time: 0.46 plus 0.35 for vertex selection. Node: 13 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 12 - elapsed time: 0.51 plus 0.34 for vertex selection. Node: 11 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 10 - elapsed time: 0.47 plus 0.35 for vertex selection. Node: 9 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 8 - elapsed time: 0.5 plus 0.35 for vertex selection. Node: 7 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 6 - elapsed time: 0.51 plus 0.36 for vertex selection. Node: 5 - elapsed time: 0.49 plus 0.36 for vertex selection. Node: 4 - elapsed time: 0.5 plus 0.35 for vertex selection. Node: 3 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 2 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 1 - elapsed time: 0.47 plus 0.34 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 5.812099e-01 4 1 3 0.000000e+00 0.000000e+00 1.016048e+00 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.016048e+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 6.267049e-01 9 1 20 7.500000e+04 1.075000e+05 1.242238e+00 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.242238e+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 2.327209e+00 12 1 10 2.500000e+00 3.361111e+01 2.361686e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.361686e+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 7.355270e-01 12 1 10 2.500000e+00 3.361111e+01 7.761691e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.761691e-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 1.325893e-02 46 1 50 0.000000e+00 1.191663e+02 6.229229e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.229229e-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 1.282692e-02 46 1 50 0.000000e+00 1.191663e+02 5.959220e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.959220e-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 3.591112e+00 103 1 3S -5.785826e+01 -6.755367e+01 5.359300e+00 309 1 4S -6.230988e+01 -6.688020e+01 6.429274e+00 412 1 5S -7.577792e+01 -6.680771e+01 7.631222e+00 515 1 6S -6.064080e+01 -6.678327e+01 8.862645e+00 618 1 7S -6.493167e+01 -6.677772e+01 9.952596e+00 721 1 15S -4.168889e+01 -6.677644e+01 1.592018e+01 1545 1 25S -4.168889e+01 -6.677644e+01 2.166181e+01 2575 1 35S -3.268889e+01 -6.677644e+01 2.771275e+01 3605 1 43S -8.368889e+01 -6.677644e+01 3.292452e+01 4429 1 53S -4.868889e+01 -6.677644e+01 3.896865e+01 5459 1 62 -6.468889e+01 -6.677644e+01 4.398147e+01 6386 1 70 -8.368889e+01 -6.677644e+01 4.900264e+01 7210 1 77S -6.468889e+01 -6.677644e+01 5.401412e+01 7931 1 85S -6.068889e+01 -6.677644e+01 5.909109e+01 8755 1 95S -6.468889e+01 -6.677644e+01 6.475604e+01 9785 1 100 -8.368889e+01 -6.677644e+01 6.715139e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.715139e+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 3.528118e-03 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.528118e-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 5.000000e+00 6.000000e+00 2.964269e+02 2 3 20 9.000000e+00 6.000000e+00 2.995989e+02 40 3 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.995989e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 6.200000e+00 ± 1.001429e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/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 5.877259e-01 48 1 20 9.000000e+00 6.000000e+00 1.034610e+00 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.034610e+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 2.075081e-01 4 1 50 0.000000e+00 0.000000e+00 5.912461e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 5.912461e-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:782 [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:2244 [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:782 [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:2244 [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 6.896105e+00 5 1 20 0.000000e+00 -1.000000e+01 7.540088e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.540088e+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 6.147912e-01 52 1 10 -2.396000e+01 -2.396000e+01 6.236150e-01 92 1 15 -4.260000e+01 -2.396000e+01 6.342051e-01 132 1 20 -2.396000e+01 -2.396000e+01 6.458859e-01 172 1 25 -5.320000e+00 -2.396000e+01 6.618910e-01 224 1 30 -5.320000e+00 -2.396000e+01 6.755099e-01 264 1 35 -2.396000e+01 -2.396000e+01 6.917720e-01 304 1 40 -2.396000e+01 -2.396000e+01 7.092710e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.092710e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 1.05s / 64.8% 11.7MiB / 60.7% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 375ms 55.1% 9.39ms 1.54MiB 21.5% 39.3KiB solve_subproblem 120 373ms 54.7% 3.11ms 1.37MiB 19.2% 11.7KiB get_dual_solution 120 45.1μs 0.0% 376ns 13.1KiB 0.2% 112B sample_scenario 40 476μs 0.1% 11.9μs 22.3KiB 0.3% 572B backward_pass 40 294ms 43.2% 7.36ms 5.41MiB 75.9% 139KiB solve_subproblem 160 259ms 37.9% 1.62ms 721KiB 9.9% 4.51KiB get_dual_solution 160 1.40ms 0.2% 8.76μs 185KiB 2.5% 1.16KiB prepare_backward_pass 160 136μs 0.0% 848ns 15.0KiB 0.2% 96.0B calculate_bound 40 11.9ms 1.8% 298μs 182KiB 2.5% 4.54KiB get_dual_solution 40 22.1μs 0.0% 552ns 4.38KiB 0.1% 112B get_dual_solution 36 12.6μs 0.0% 351ns 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 8.248541e-01 52 1 10 -2.396000e+01 -2.396000e+01 8.351011e-01 92 1 15 -2.396000e+01 -2.396000e+01 8.486981e-01 132 1 20 -4.260000e+01 -2.396000e+01 8.647230e-01 172 1 25 -5.320000e+00 -2.396000e+01 8.862779e-01 224 1 30 -2.396000e+01 -2.396000e+01 9.069891e-01 264 1 35 -2.396000e+01 -2.396000e+01 9.296780e-01 304 1 40 -5.320000e+00 -2.396000e+01 9.582241e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.582241e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 965ms / 95.9% 13.6MiB / 94.4% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 566ms 61.2% 14.2ms 1.54MiB 12.0% 39.3KiB solve_subproblem 120 564ms 60.9% 4.70ms 1.37MiB 10.7% 11.7KiB get_dual_solution 120 58.3μs 0.0% 486ns 13.1KiB 0.1% 112B sample_scenario 40 481μs 0.1% 12.0μs 22.5KiB 0.2% 575B backward_pass 40 346ms 37.3% 8.64ms 11.1MiB 86.6% 284KiB solve_subproblem 160 272ms 29.4% 1.70ms 722KiB 5.5% 4.51KiB get_dual_solution 160 241ms 26.1% 1.51ms 185KiB 1.4% 1.16KiB prepare_backward_pass 160 184μs 0.0% 1.15μs 15.0KiB 0.1% 96.0B calculate_bound 40 14.0ms 1.5% 350μs 183KiB 1.4% 4.58KiB get_dual_solution 40 19.0μs 0.0% 476ns 4.38KiB 0.0% 112B get_dual_solution 36 30.1μs 0.0% 835ns 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 6.736860e-01 5 1 2 -2.500000e+00 -2.000000e+00 6.763041e-01 14 1 3 -1.000000e+00 -2.000000e+00 6.785252e-01 19 1 4 -1.000000e+00 -2.000000e+00 6.795731e-01 24 1 5 -1.000000e+00 -2.000000e+00 6.939790e-01 29 1 6 -3.000000e+00 -2.000000e+00 6.961591e-01 34 1 7 -1.000000e+00 -2.000000e+00 6.973331e-01 39 1 8 -1.000000e+00 -2.000000e+00 6.987340e-01 44 1 9 -3.000000e+00 -2.000000e+00 6.997061e-01 49 1 10 -1.000000e+00 -2.000000e+00 7.008550e-01 54 1 11 -3.000000e+00 -2.000000e+00 7.027011e-01 59 1 12 -3.000000e+00 -2.000000e+00 7.037532e-01 64 1 13 -1.000000e+00 -2.000000e+00 7.049372e-01 69 1 14 -1.000000e+00 -2.000000e+00 7.067802e-01 74 1 15 -3.000000e+00 -2.000000e+00 7.077310e-01 79 1 16 -1.000000e+00 -2.000000e+00 7.088990e-01 84 1 17 -3.000000e+00 -2.000000e+00 7.108321e-01 89 1 18 -3.000000e+00 -2.000000e+00 7.119751e-01 94 1 19 -1.000000e+00 -2.000000e+00 7.133372e-01 99 1 20 -3.000000e+00 -2.000000e+00 7.149401e-01 104 1 21 -1.000000e+00 -2.000000e+00 7.170992e-01 113 1 22 -1.000000e+00 -2.000000e+00 7.186830e-01 118 1 23 -3.000000e+00 -2.000000e+00 7.206230e-01 123 1 24 -3.000000e+00 -2.000000e+00 7.221351e-01 128 1 25 -1.000000e+00 -2.000000e+00 7.235332e-01 133 1 26 -3.000000e+00 -2.000000e+00 7.251451e-01 138 1 27 -3.000000e+00 -2.000000e+00 7.275250e-01 143 1 28 -1.000000e+00 -2.000000e+00 7.291002e-01 148 1 29 -3.000000e+00 -2.000000e+00 7.306702e-01 153 1 30 -3.000000e+00 -2.000000e+00 7.319701e-01 158 1 31 -1.000000e+00 -2.000000e+00 7.333791e-01 163 1 32 -1.000000e+00 -2.000000e+00 7.356632e-01 168 1 33 -1.000000e+00 -2.000000e+00 7.373581e-01 173 1 34 -3.000000e+00 -2.000000e+00 7.389960e-01 178 1 35 -1.000000e+00 -2.000000e+00 7.425470e-01 183 1 36 -3.000000e+00 -2.000000e+00 7.444642e-01 188 1 37 -1.000000e+00 -2.000000e+00 7.461851e-01 193 1 38 -1.000000e+00 -2.000000e+00 7.476351e-01 198 1 39 -1.000000e+00 -2.000000e+00 7.493131e-01 203 1 40 -1.000000e+00 -2.000000e+00 7.511961e-01 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.511961e-01 total solves : 208 best bound : -2.000000e+00 simulation ci : -1.812500e+00 ± 3.171441e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: Hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+00] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.000000e+01 1.882708e+01 1.086474e+00 51 1 19 1.321040e+02 2.223414e+02 2.122756e+00 3549 1 30 2.138334e+03 2.336430e+02 3.951146e+00 7674 1 38 8.025312e+02 2.352957e+02 5.360147e+00 10194 1 45 4.103715e+01 2.358381e+02 6.384219e+00 11835 1 54 1.830901e+02 2.360657e+02 7.485590e+00 13446 1 63 1.493193e+03 2.362190e+02 9.357675e+00 15909 1 90 2.500000e+00 2.363897e+02 1.436311e+01 21030 1 100 4.969839e+02 2.364135e+02 1.735214e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.735214e+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 1.913157e+00 1400 1 20 -4.764789e+00 -4.394789e+00 2.186476e+00 2800 1 30 -4.672487e+00 -4.377000e+00 2.474467e+00 4200 1 40 -4.483495e+00 -4.370632e+00 2.766685e+00 5600 1 50 -4.167321e+00 -4.364999e+00 3.068096e+00 7000 1 60 -4.362455e+00 -4.358864e+00 3.370739e+00 8400 1 70 -4.849916e+00 -4.355337e+00 3.674090e+00 9800 1 80 -4.861568e+00 -4.353006e+00 3.990621e+00 11200 1 90 -4.268264e+00 -4.350407e+00 4.425506e+00 12600 1 100 -4.539897e+00 -4.348641e+00 4.770811e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.770811e+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 1.616188e+00 1050 1 20 -1.529197e+00 -1.471817e+00 1.718504e+00 1600 1 30 -1.410768e+00 -1.471408e+00 1.936081e+00 2650 1 40 -1.596461e+00 -1.471258e+00 2.047404e+00 3200 1 50 -1.002277e+00 -1.471216e+00 2.268782e+00 4250 1 60 -1.085156e+00 -1.471164e+00 2.383457e+00 4800 1 70 -1.391746e+00 -1.471164e+00 2.601052e+00 5850 1 80 -1.448703e+00 -1.471132e+00 2.723206e+00 6400 1 90 -1.488989e+00 -1.471087e+00 2.946768e+00 7450 1 100 -1.564260e+00 -1.471075e+00 3.069772e+00 8000 1 110 -1.738157e+00 -1.471075e+00 3.185585e+00 8550 1 120 -1.591292e+00 -1.471075e+00 3.309313e+00 9100 1 130 -1.271481e+00 -1.471075e+00 3.431029e+00 9650 1 140 -1.249746e+00 -1.471075e+00 3.564335e+00 10200 1 150 -1.536222e+00 -1.471075e+00 3.698444e+00 10750 1 160 -1.565422e+00 -1.471075e+00 3.841481e+00 11300 1 170 -1.631076e+00 -1.471075e+00 3.981984e+00 11850 1 180 -1.494909e+00 -1.471075e+00 4.118690e+00 12400 1 182 -9.083563e-01 -1.471075e+00 4.142050e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.142050e+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 5.634098e-01 54 1 20 3.336455e+05 3.402383e+05 5.790260e-01 104 1 30 3.993519e+05 3.403155e+05 5.939460e-01 158 1 40 3.337559e+05 3.403155e+05 6.076660e-01 208 1 48 3.337559e+05 3.403155e+05 6.221719e-01 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.221719e-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 8.321550e-01 92 1 20 4.506600e+05 4.054833e+05 8.606191e-01 172 1 30 3.959476e+05 4.067125e+05 8.849339e-01 264 1 40 4.497721e+05 4.067125e+05 9.110889e-01 344 1 47 3.959476e+05 4.067125e+05 9.336250e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.336250e-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 7.790713e+00 14 1 2 7.566889e+03 3.171195e+03 8.905401e+00 136 1 40 2.308500e+03 4.074139e+03 9.160854e+00 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.160854e+00 total solves : 776 best bound : 4.074139e+03 simulation ci : 4.224313e+03 ± 6.692189e+02 numeric issues : 0 ------------------------------------------------------------------- [ Info: air_conditioning.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 7.000000e+04 6.250000e+04 2.487856e+00 8 1 5L 4.000000e+04 6.250000e+04 3.628090e+00 52 1 11L 4.000000e+04 6.250000e+04 4.733620e+00 100 1 17L 4.000000e+04 6.250000e+04 5.835144e+00 148 1 20L 6.000000e+04 6.250000e+04 6.486082e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.486082e+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 5.522311e-01 8 1 15 5.500000e+04 6.250000e+04 1.589181e+00 132 1 20 4.000000e+04 6.250000e+04 1.958222e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.958222e+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 1.472875e+00 5 1 10 4.000000e+04 6.250000e+04 2.051170e+00 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.051170e+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 8.938088e-01 6 1 20L 9.000000e+00 9.000000e+00 1.025097e+00 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.025097e+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 2.392024e+00 87 1 10 -1.109375e+01 2.605769e-01 2.403828e+00 142 1 15 3.105797e+00 5.434132e-01 2.417529e+00 197 1 20 -2.463349e+01 1.503415e+00 2.431852e+00 252 1 25 -1.421085e-14 1.514085e+00 2.445247e+00 307 1 30 4.864000e+01 1.514085e+00 4.524740e+00 394 1 35 4.864000e+01 1.514085e+00 4.539530e+00 449 1 40 -8.870299e+00 1.514085e+00 4.556686e+00 504 1 45 -1.428571e+00 1.514085e+00 4.972060e+00 559 1 48 -1.428571e+00 1.514085e+00 5.006070e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.006070e+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 2.680744e+00 278 1 20 1.440356e+01 1.278425e+00 2.720216e+00 428 1 30 8.388546e+00 1.278425e+00 2.791072e+00 706 1 40 6.666667e-03 1.278410e+00 2.836037e+00 856 1 50 -5.614035e+00 1.278410e+00 2.912782e+00 1134 1 60 1.426676e+01 1.278410e+00 2.966433e+00 1284 1 64 1.261296e+01 1.278410e+00 2.987957e+00 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.987957e+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 1.329980e+00 278 1 20 1.111084e+01 1.278410e+00 1.390944e+00 428 1 30 2.293779e+01 1.278410e+00 1.490313e+00 706 1 40 1.426676e+01 1.278410e+00 1.587337e+00 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.587337e+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 6.276085e+00 900 1 20 6.374753e+00 1.361934e+01 6.695363e+00 1720 1 30 2.848217e+01 1.624016e+01 7.676366e+00 3036 1 40 1.973944e+01 1.776547e+01 8.945954e+00 4192 1 50 4.000000e+00 1.889360e+01 9.839827e+00 5020 1 60 1.142478e+01 1.907862e+01 1.076705e+01 5808 1 70 9.386421e+00 1.961295e+01 1.167189e+01 6540 1 80 5.667851e+01 1.890911e+01 1.239570e+01 7088 1 90 3.740597e+01 1.993139e+01 1.407893e+01 8180 1 100 9.867183e+00 2.001688e+01 1.488074e+01 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.488074e+01 total solves : 8664 best bound : 2.001688e+01 simulation ci : 2.301336e+01 ± 4.670816e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: biobjective_hydro.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 3.950723e+00 36 1 10 0.000000e+00 0.000000e+00 4.013108e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.013108e+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 8.944988e-03 407 1 10 2.850000e+02 5.728212e+02 8.565283e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.565283e-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 8.902073e-03 778 1 10 2.825000e+02 3.465177e+02 8.812904e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.812904e-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 8.776188e-03 1149 1 10 2.587500e+02 2.052799e+02 8.486199e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.486199e-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 9.772062e-03 1520 1 10 2.875000e+02 4.661908e+02 9.450507e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.450507e-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 9.481907e-03 1891 1 10 1.000000e+02 1.129771e+02 8.496499e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.496499e-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 9.984016e-03 2262 1 10 1.625000e+02 2.794553e+02 9.493589e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.493589e-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 1.073098e-02 2633 1 10 5.487500e+02 4.077574e+02 9.809995e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.809995e-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 1.072192e-02 3004 1 10 6.771875e+02 5.210100e+02 9.936810e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.936810e-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 9.448051e-03 3375 1 10 5.312500e+01 5.938345e+01 8.655190e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.655190e-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 2.694052e+00 235 1 10 1.000000e+01 9.159200e+00 3.205071e+00 310 1 15 1.000000e+01 9.159200e+00 3.771531e+00 385 1 20 1.000000e+01 9.159200e+00 4.319978e+00 460 1 25 1.000000e+01 9.159200e+00 7.249523e+00 695 1 30 4.000000e+00 9.159200e+00 7.770497e+00 770 1 35 1.000000e+01 9.159200e+00 8.286506e+00 845 1 40 1.000000e+01 9.159200e+00 8.856493e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.856493e+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 2.377658e+00 510 1 20 1.000000e+01 6.834387e+00 4.163205e+00 720 1 30 7.000000e+00 6.834387e+00 8.028463e+00 1230 1 40 1.000000e+01 6.823805e+00 9.744221e+00 1440 1 50 3.000000e+00 6.823805e+00 1.393665e+01 1950 1 60 2.000000e+00 6.823805e+00 1.572611e+01 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.572611e+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 1.241439e+01 920 1 20 6.049875e+06 2.075240e+06 1.527261e+01 1340 1 30 5.496647e+05 2.078257e+06 2.644130e+01 2260 1 40 3.985383e+04 2.078257e+06 2.910333e+01 2680 1 50 2.994548e+05 2.078257e+06 4.006643e+01 3600 1 60 3.799457e+06 2.078257e+06 4.288873e+01 4020 1 61 3.549665e+06 2.078257e+06 4.316902e+01 4062 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.316902e+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 3.295797e+01 920 1 20L 2.799668e+06 2.079457e+06 5.426584e+01 1340 1 30L 3.799443e+06 2.079457e+06 8.531050e+01 2260 1 40L 4.299882e+06 2.079457e+06 1.069470e+02 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.069470e+02 total solves : 2680 best bound : 2.079457e+06 simulation ci : 1.602238e+06 ± 4.944385e+05 numeric issues : 0 ------------------------------------------------------------------- [ Info: hydro_valley.jl [ Info: infinite_horizon_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.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 3.209841e+00 1914 1 200 0.000000e+00 1.191645e+02 3.671476e+00 3840 1 300 7.500000e+01 1.191666e+02 4.211716e+00 5738 1 328 2.500000e+00 1.191667e+02 4.331986e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.331986e+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 9.665549e-01 2806 1 200 0.000000e+00 1.191666e+02 1.606651e+00 4749 1 287 5.000000e+00 1.191667e+02 2.080579e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.080579e+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 4.191561e-01 1033 1 20 8.000000e+00 2.000000e+01 4.525111e-01 1209 1 30 1.200000e+01 2.000000e+01 6.059401e-01 2304 1 40 3.000000e+01 2.000000e+01 7.126641e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.126641e-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 1.060667e+00 35 1 10 7.500000e+02 2.935390e+03 1.137673e+00 350 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.137673e+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: 0.36 plus 0.57 for vertex selection. Node: 2 - elapsed time: 0.31 plus 0.28 for vertex selection. Node: 1 - elapsed time: 0.33 plus 0.17 for vertex selection. First-stage upper bound: 2969.680973503913 Total time for upper bound: 2.02212857 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 1.995499e-01 3 1 40 2.000000e+00 2.000000e+00 3.819618e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.819618e-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 1.638236e+00 1350 1 20 5.062500e+00 4.110713e+00 1.884020e+00 2700 1 30 4.500000e+00 4.104200e+00 2.152630e+00 4050 1 40 3.812500e+00 4.102669e+00 2.422185e+00 5400 1 50 4.725000e+00 4.095504e+00 2.696633e+00 6750 1 60 4.050000e+00 4.092999e+00 2.978857e+00 8100 1 70 4.606250e+00 4.091524e+00 3.271951e+00 9450 1 80 3.875000e+00 4.089694e+00 3.569005e+00 10800 1 90 3.750000e+00 4.089490e+00 4.282382e+00 12150 1 100 5.125000e+00 4.087894e+00 4.614483e+00 13500 1 110 4.500000e+00 4.087478e+00 4.949717e+00 14850 1 120 3.650000e+00 4.086704e+00 5.278227e+00 16200 1 130 4.406250e+00 4.086063e+00 5.601260e+00 17550 1 140 3.375000e+00 4.085981e+00 5.896966e+00 18900 1 150 3.000000e+00 4.085945e+00 6.205745e+00 20250 1 160 3.812500e+00 4.085838e+00 6.514523e+00 21600 1 170 4.250000e+00 4.085728e+00 6.831910e+00 22950 1 180 3.243750e+00 4.085593e+00 7.176018e+00 24300 1 190 4.306250e+00 4.085487e+00 7.515455e+00 25650 1 200 5.237500e+00 4.085446e+00 7.875156e+00 27000 1 210 4.500000e+00 4.085441e+00 8.228023e+00 28350 1 220 3.612500e+00 4.085405e+00 8.595497e+00 29700 1 230 3.700000e+00 4.085382e+00 8.949394e+00 31050 1 240 3.437500e+00 4.085254e+00 9.305998e+00 32400 1 250 4.100000e+00 4.085115e+00 9.673672e+00 33750 1 260 3.000000e+00 4.084973e+00 1.004517e+01 35100 1 270 4.918750e+00 4.084943e+00 1.041932e+01 36450 1 280 2.756250e+00 4.084920e+00 1.080828e+01 37800 1 290 3.737500e+00 4.084868e+00 1.121360e+01 39150 1 300 5.750000e+00 4.084868e+00 1.162183e+01 40500 1 310 5.156250e+00 4.084858e+00 1.203385e+01 41850 1 320 3.131250e+00 4.084855e+00 1.242338e+01 43200 1 330 4.125000e+00 4.084846e+00 1.281742e+01 44550 1 340 5.875000e+00 4.084820e+00 1.322391e+01 45900 1 350 4.587500e+00 4.084810e+00 1.362814e+01 47250 1 360 5.087500e+00 4.084805e+00 1.404616e+01 48600 1 370 4.393750e+00 4.084802e+00 1.460401e+01 49950 1 380 4.750000e+00 4.084792e+00 1.499230e+01 51300 1 390 4.437500e+00 4.084785e+00 1.538684e+01 52650 1 400 4.181250e+00 4.084785e+00 1.578007e+01 54000 1 410 3.650000e+00 4.084777e+00 1.616151e+01 55350 1 420 3.750000e+00 4.084769e+00 1.656164e+01 56700 1 430 3.725000e+00 4.084762e+00 1.702570e+01 58050 1 440 4.218750e+00 4.084751e+00 1.750030e+01 59400 1 450 5.500000e+00 4.084751e+00 1.796833e+01 60750 1 460 3.637500e+00 4.084747e+00 1.847098e+01 62100 1 470 2.993750e+00 4.084743e+00 1.894724e+01 63450 1 480 5.237500e+00 4.084743e+00 1.943380e+01 64800 1 490 4.212500e+00 4.084743e+00 1.992100e+01 66150 1 492 4.062500e+00 4.084743e+00 2.002509e+01 66420 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.002509e+01 total solves : 66420 best bound : 4.084743e+00 simulation ci : 4.084057e+00 ± 6.752519e-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 3.625000e+00 5.041677e+00 1.469099e+00 1350 1 20 4.343750e+00 4.339734e+00 2.742708e+00 2700 1 30 3.368750e+00 4.337296e+00 4.088455e+00 4050 1 40 4.225000e+00 4.336226e+00 5.483486e+00 5400 1 50 3.812500e+00 4.050531e+00 7.423863e+00 6750 1 60 4.875000e+00 4.049347e+00 9.640598e+00 8100 1 70 4.662500e+00 4.045949e+00 1.235139e+01 9450 1 80 4.375000e+00 4.040011e+00 1.468300e+01 10800 1 90 5.156250e+00 4.038649e+00 1.725908e+01 12150 1 100 2.831250e+00 4.038562e+00 2.017334e+01 13500 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.017334e+01 total solves : 13500 best bound : 4.038562e+00 simulation ci : 4.098688e+00 ± 1.370698e-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 1.935507e+01 1680 1 20 2.078810e+00 1.166281e+00 2.093995e+01 2560 1 30 3.973033e+00 1.166907e+00 2.270211e+01 3440 1 40 3.706337e+00 1.167312e+00 3.878290e+01 5120 1 50 3.158565e+00 1.167416e+00 4.037765e+01 6000 1 60 3.642642e+00 1.167416e+00 5.686143e+01 7680 1 70 3.451253e+00 1.167416e+00 5.869020e+01 8560 1 71 2.984727e+00 1.167416e+00 5.883958e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.883958e+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 1.066606e+00 78 1 20 -4.000000e+01 -5.809615e+01 1.761559e+00 148 1 30 -4.000000e+01 -5.809615e+01 2.516578e+00 226 1 40 -4.700000e+01 -5.809615e+01 3.199553e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.199553e+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 1.106427e+00 138 1 20 -4.000000e+01 -6.196125e+01 1.816472e+00 258 1 30 -7.500000e+01 -6.196125e+01 2.816570e+00 396 1 40 -4.000000e+01 -6.196125e+01 3.570815e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.570815e+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 1.831895e+00 462 1 20 -5.600000e+01 -6.546793e+01 2.585901e+00 852 1 30 -4.000000e+01 -6.546793e+01 4.771886e+00 1314 1 40 -4.000000e+01 -6.546793e+01 5.542761e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.542761e+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 1.523573e+00 11 1 7L 6.000000e+00 8.000000e+00 2.696307e+00 158 1 12L 6.000000e+00 8.000000e+00 3.803333e+00 213 1 17L 6.000000e+00 8.000000e+00 5.011329e+00 268 1 21L 1.200000e+01 8.000000e+00 6.628318e+00 393 1 26L 6.000000e+00 8.000000e+00 7.690324e+00 448 1 31L 1.200000e+01 8.000000e+00 8.822341e+00 503 1 40L 6.000000e+00 8.000000e+00 1.095135e+01 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.095135e+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 9.231479e-01 6 1 40 1.093500e+05 1.083900e+05 9.743550e-01 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.743550e-01 total solves : 240 best bound : 1.083900e+05 simulation ci : 9.772505e+04 ± 1.969816e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: vehicle_location.jl Test Summary: | Pass Fail Total Time SDDP.jl | 2453 2 2455 37m54.3s Experimental.jl | 35 35 4m12.3s Inner.jl | 25 25 5m23.0s MSPFormat.jl | 51 51 20.4s algorithm.jl | 40 40 1m16.3s binary_expansion.jl | 38 38 3.2s deterministic_equivalent.jl | 21 21 31.0s modeling_aids.jl | 47 47 18.1s user_interface.jl | 119 119 1m04.3s backward_sampling_schemes.jl | 1203 1203 6.5s bellman_functions.jl | 45 45 57.9s duality_handlers.jl | 362 362 3m13.7s forward_passes.jl | 40 40 23.7s local_improvement_search.jl | 12 12 21.7s parallel_schemes.jl | 19 19 7m51.5s risk_measures.jl | 91 91 15.4s sampling_schemes.jl | 158 158 22.1s stopping_rules.jl | 40 40 13.8s threaded.jl | 0 0.4s value_functions.jl | 28 28 26.9s visualization.jl | 9 2 11 1m08.2s test_PublicationPlot | 5 5 20.5s test_PublicationPlot_different_lengths | 1 1 0.8s test_SpaghettiPlot | 3 2 5 8.4s FAST_hydro_thermal.jl | 3 3 12.9s FAST_production_management.jl | 2 2 6.0s FAST_quickstart.jl | 2 2 2.4s Hydro_thermal.jl | 0 22.7s StochDynamicProgramming.jl_multistock.jl | 3 3 16.1s StochDynamicProgramming.jl_stock.jl | 3 3 6.6s StructDualDynProg.jl_prob5.2_2stages.jl | 1 1 4.3s StructDualDynProg.jl_prob5.2_3stages.jl | 2 2 3.4s agriculture_mccardle_farm.jl | 2 2 15.6s air_conditioning.jl | 6 6 10.8s air_conditioning_forward.jl | 2 2 3.5s all_blacks.jl | 1 1 2.3s asset_management_simple.jl | 1 1 6.4s asset_management_stagewise.jl | 2 2 7.0s belief.jl | 1 1 20.0s biobjective_hydro.jl | 10 10 8.5s booking_management.jl | 2 2 33.4s generation_expansion.jl | 2 2 2m49.4s hydro_valley.jl | 9 9 23.3s infinite_horizon_hydro_thermal.jl | 4 4 10.3s infinite_horizon_trivial.jl | 1 1 1.6s inner_hydro_1d.jl | 1 1 10.7s no_strong_duality.jl | 1 1 1.6s objective_state_newsvendor.jl | 4 4 51.0s sldp_example_one.jl | 1 1 1m15.8s sldp_example_two.jl | 3 3 16.3s stochastic_all_blacks.jl | 1 1 15.0s the_farmers_problem.jl | 0 5.6s vehicle_location.jl | 0 0.1s RNG of the outermost testset: Xoshiro(0x3831f892e3f87f55, 0x0f6272ab69a6d58d, 0x64c491188a6fe934, 0xbdc86f737677c9a6, 0x8eab32381263118a) 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 2284.57s 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:309 [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 2495.77s: package has test failures