Package evaluation to test SDDP on Julia 1.14.0-DEV.2275 (3ea3bac2a3*) started at 2026-06-04T19:01:55.109 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 15.89s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [f4570300] + SDDP v1.13.2 Updating `~/.julia/environments/v1.14/Manifest.toml` [d1d4a3ce] + BitFlags v0.1.10 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [f0e56b4a] + ConcurrentUtilities v2.5.1 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.16.0 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v1.3.3 ⌅ [cd3eb016] + HTTP v1.11.0 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.6.1 [4076af6c] + JuMP v1.30.1 ⌅ [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.51.1 [739be429] + MbedTLS v1.1.10 [d8a4904e] + MutableArithmetics v1.8.0 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.6.1 ⌅ [bac558e1] + OrderedCollections v1.8.2 [69de0a69] + Parsers v2.8.4 [aea7be01] + PrecompileTools v1.3.4 [21216c6a] + Preferences v1.5.2 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.13.2 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.8.0 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [ec057cc2] + StructUtils v2.8.2 [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 v1.14.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [ca575930] + NetworkOptions v1.3.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.13.0 [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 v1.5.2+0 [14a3606d] + MozillaCACerts_jll v2026.5.14 [4536629a] + OpenBLAS_jll v0.3.33+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.6+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [8e850b90] + libblastrampoline_jll v5.15.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 5.37s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling project... 8.7 s ✓ MathOptIIS 26.0 s ✓ SDDP 41.1 s ✓ HiGHS 3 dependencies successfully precompiled in 85 seconds. 207 already precompiled. Precompilation completed after 106.15s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_HSJUIq/Project.toml` ⌅ [87dc4568] HiGHS v1.22.2 [b6b21f68] Ipopt v1.14.3 [682c06a0] JSON v1.6.1 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.6 [f4570300] SDDP v1.13.2 [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_HSJUIq/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [d1d4a3ce] BitFlags v0.1.10 [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 [f0e56b4a] ConcurrentUtilities v2.5.1 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.5 [8bb1440f] DelimitedFiles v1.9.1 [163ba53b] DiffResults v1.1.0 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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: 0.42 plus 10.24 for vertex selection. Node: 2 - elapsed time: 0.31 plus 0.3 for vertex selection. Node: 1 - elapsed time: 0.31 plus 0.3 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 11.888367176000001 ┌ Warning: You must select an optimizer for performing vertex selection. └ @ SDDP.Inner ~/.julia/packages/SDDP/R1Ovj/src/Inner.jl:1049 Node: 19 - elapsed time: 0.37 plus 0.35 for vertex selection. Node: 18 - elapsed time: 0.48 plus 0.36 for vertex selection. Node: 17 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 16 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 15 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 14 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 13 - elapsed time: 0.49 plus 0.37 for vertex selection. Node: 12 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 11 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 10 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 9 - elapsed time: 0.47 plus 0.35 for vertex selection. Node: 8 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 7 - elapsed time: 0.48 plus 0.35 for vertex selection. Node: 6 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 5 - elapsed time: 0.47 plus 0.35 for vertex selection. Node: 4 - elapsed time: 0.49 plus 0.35 for vertex selection. Node: 3 - elapsed time: 0.47 plus 0.35 for vertex selection. Node: 2 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 1 - elapsed time: 0.49 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/R1Ovj/src/algorithm.jl:402 [ 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, 2017-26 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.AffExpr in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [2, 2] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- † 1 0.000000e+00 0.000000e+00 6.003430e-01 4 1 3 0.000000e+00 0.000000e+00 1.141099e+00 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.141099e+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, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [4, 4] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.100000e+05 1.075000e+05 5.183191e-01 9 1 20 7.500000e+04 1.075000e+05 1.218550e+00 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.218550e+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/R1Ovj/src/algorithm.jl:1182 ┌ 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/R1Ovj/src/algorithm.jl:1182 [ 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/R1Ovj/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, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.138889e+01 1.869089e+00 12 1 10 2.500000e+00 3.361111e+01 1.896475e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.896475e+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, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.083333e+01 5.491199e-01 12 1 10 2.500000e+00 3.361111e+01 6.351609e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.351609e-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, 2017-26 ------------------------------------------------------------------- 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 1.110888e-02 46 1 50 0.000000e+00 1.191663e+02 5.189490e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.189490e-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, 2017-26 ------------------------------------------------------------------- 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 1.096392e-02 46 1 50 0.000000e+00 1.191663e+02 5.775471e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.775471e-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, 2017-26 ------------------------------------------------------------------- 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 3.672829e+00 103 1 3S -5.785826e+01 -6.755367e+01 5.554189e+00 309 1 4S -6.230988e+01 -6.688020e+01 6.587644e+00 412 1 5S -7.577792e+01 -6.680771e+01 7.743019e+00 515 1 6S -6.064080e+01 -6.678327e+01 8.895246e+00 618 1 7S -6.493167e+01 -6.677772e+01 9.927948e+00 721 1 15S -4.168889e+01 -6.677644e+01 1.559609e+01 1545 1 25S -4.168889e+01 -6.677644e+01 2.133209e+01 2575 1 35S -3.268889e+01 -6.677644e+01 2.719140e+01 3605 1 45S -4.168889e+01 -6.677644e+01 3.291384e+01 4635 1 55S -4.868889e+01 -6.677644e+01 3.865496e+01 5665 1 65S -4.168889e+01 -6.677644e+01 4.449865e+01 6695 1 75S -8.368889e+01 -6.677644e+01 5.025863e+01 7725 1 85S -6.068889e+01 -6.677644e+01 5.597273e+01 8755 1 95S -6.468889e+01 -6.677644e+01 6.187179e+01 9785 1 100 -8.368889e+01 -6.677644e+01 6.413075e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.413075e+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, 2017-26 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 3.000000e+00 6.000000e+00 1.898599e-02 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.898599e-02 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/R1Ovj/src/algorithm.jl:1182 [ 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, 2017-26 ------------------------------------------------------------------- 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 3.000000e+00 6.000000e+00 3.371591e+02 2 4 20 5.000000e+00 6.000000e+00 3.403611e+02 40 3 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.403611e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 6.300000e+00 ± 9.549212e-01 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/R1Ovj/src/algorithm.jl:1182 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 3.743148e-01 48 1 20 9.000000e+00 6.000000e+00 6.475430e-01 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.475430e-01 total solves : 162 best bound : 6.000000e+00 simulation ci : 5.900000e+00 ± 9.633534e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: risk_measures.jl ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/R1Ovj/src/plugins/risk_measures.jl:529 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/R1Ovj/src/plugins/risk_measures.jl:529 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/R1Ovj/src/plugins/risk_measures.jl:529 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 1.615078e-01 4 1 50 0.000000e+00 0.000000e+00 4.386239e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 4.386239e-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/R1Ovj/src/plugins/stopping_rules.jl:133 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/R1Ovj/src/plugins/stopping_rules.jl:133 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/R1Ovj/src/plugins/stopping_rules.jl:133 [ Info: threaded.jl [ Info: value_functions.jl [ Info: visualization.jl ┌ Warning: `SDDP.save` is deprecated. Use `SDDP.plot` instead. │ caller = test_SpaghettiPlot() at visualization.jl:49 └ @ Main.TestVisualization ~/.julia/packages/SDDP/R1Ovj/test/visualization/visualization.jl:49 [ Info: FAST_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+00] bounds range [8e+00, 8e+00] rhs range [6e+00, 6e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -2.000000e+01 -1.000000e+01 7.017427e+00 5 1 20 0.000000e+00 -1.000000e+01 7.646277e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.646277e+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, 2017-26 ------------------------------------------------------------------- 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 3.948560e-01 52 1 10 -2.396000e+01 -2.396000e+01 4.019821e-01 92 1 15 -4.260000e+01 -2.396000e+01 4.100130e-01 132 1 20 -2.396000e+01 -2.396000e+01 4.199729e-01 172 1 25 -5.320000e+00 -2.396000e+01 4.319100e-01 224 1 30 -5.320000e+00 -2.396000e+01 4.434180e-01 264 1 35 -2.396000e+01 -2.396000e+01 4.540551e-01 304 1 40 -2.396000e+01 -2.396000e+01 4.670420e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.670420e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 811ms / 55.6% 10.7MiB / 56.6% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 238ms 52.7% 5.95ms 648KiB 10.5% 16.2KiB solve_subproblem 120 236ms 52.2% 1.96ms 475KiB 7.7% 3.96KiB get_dual_solution 120 48.7μs 0.0% 406ns 13.1KiB 0.2% 112B sample_scenario 40 421μs 0.1% 10.5μs 22.3KiB 0.4% 572B backward_pass 40 204ms 45.2% 5.09ms 5.23MiB 86.5% 134KiB solve_subproblem 160 180ms 39.9% 1.13ms 721KiB 11.6% 4.51KiB get_dual_solution 160 1.39ms 0.3% 8.68μs 185KiB 3.0% 1.16KiB prepare_backward_pass 160 125μs 0.0% 784ns 15.0KiB 0.2% 96.0B calculate_bound 40 9.40ms 2.1% 235μs 182KiB 2.9% 4.54KiB get_dual_solution 40 17.4μs 0.0% 436ns 4.38KiB 0.1% 112B get_dual_solution 36 12.1μs 0.0% 337ns 3.94KiB 0.1% 112B ──────────────────────────────────────────────────────────────────────────────────── ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -2.396000e+01 -2.396000e+01 5.075519e-01 52 1 10 -2.396000e+01 -2.396000e+01 5.143120e-01 92 1 15 -2.396000e+01 -2.396000e+01 5.235500e-01 132 1 20 -4.260000e+01 -2.396000e+01 5.340900e-01 172 1 25 -5.320000e+00 -2.396000e+01 5.479069e-01 224 1 30 -2.396000e+01 -2.396000e+01 5.609851e-01 264 1 35 -2.396000e+01 -2.396000e+01 5.748000e-01 304 1 40 -5.320000e+00 -2.396000e+01 5.917521e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.917521e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 598ms / 97.0% 12.3MiB / 93.8% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 346ms 59.6% 8.65ms 648KiB 5.5% 16.2KiB solve_subproblem 120 344ms 59.3% 2.87ms 475KiB 4.0% 3.96KiB get_dual_solution 120 40.2μs 0.0% 335ns 13.1KiB 0.1% 112B sample_scenario 40 401μs 0.1% 10.0μs 22.5KiB 0.2% 575B backward_pass 40 224ms 38.7% 5.61ms 10.7MiB 92.9% 274KiB solve_subproblem 160 153ms 26.3% 954μs 722KiB 6.1% 4.51KiB get_dual_solution 160 1.16ms 0.2% 7.24μs 185KiB 1.6% 1.16KiB prepare_backward_pass 160 134μs 0.0% 835ns 15.0KiB 0.1% 96.0B calculate_bound 40 9.87ms 1.7% 247μs 183KiB 1.6% 4.58KiB get_dual_solution 40 16.9μs 0.0% 423ns 4.38KiB 0.0% 112B get_dual_solution 36 11.3μs 0.0% 314ns 3.94KiB 0.0% 112B ──────────────────────────────────────────────────────────────────────────────────── [ Info: FAST_quickstart.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 3.889999e-01 5 1 2 -2.500000e+00 -2.000000e+00 5.206480e-01 14 1 3 -1.000000e+00 -2.000000e+00 5.214379e-01 19 1 4 -1.000000e+00 -2.000000e+00 5.221219e-01 24 1 5 -1.000000e+00 -2.000000e+00 5.535009e-01 29 1 6 -3.000000e+00 -2.000000e+00 5.548389e-01 34 1 7 -1.000000e+00 -2.000000e+00 5.555820e-01 39 1 8 -1.000000e+00 -2.000000e+00 5.562940e-01 44 1 9 -3.000000e+00 -2.000000e+00 5.570290e-01 49 1 10 -1.000000e+00 -2.000000e+00 5.579510e-01 54 1 11 -3.000000e+00 -2.000000e+00 5.594270e-01 59 1 12 -3.000000e+00 -2.000000e+00 5.608070e-01 64 1 13 -1.000000e+00 -2.000000e+00 5.615029e-01 69 1 14 -1.000000e+00 -2.000000e+00 5.623951e-01 74 1 15 -3.000000e+00 -2.000000e+00 5.637231e-01 79 1 16 -1.000000e+00 -2.000000e+00 5.644541e-01 84 1 17 -3.000000e+00 -2.000000e+00 5.652189e-01 89 1 18 -3.000000e+00 -2.000000e+00 5.660911e-01 94 1 19 -1.000000e+00 -2.000000e+00 5.675371e-01 99 1 20 -3.000000e+00 -2.000000e+00 5.687771e-01 104 1 21 -1.000000e+00 -2.000000e+00 5.702381e-01 113 1 22 -1.000000e+00 -2.000000e+00 5.717659e-01 118 1 23 -3.000000e+00 -2.000000e+00 5.725961e-01 123 1 24 -3.000000e+00 -2.000000e+00 5.734041e-01 128 1 25 -1.000000e+00 -2.000000e+00 5.743849e-01 133 1 26 -3.000000e+00 -2.000000e+00 5.760651e-01 138 1 27 -3.000000e+00 -2.000000e+00 5.773661e-01 143 1 28 -1.000000e+00 -2.000000e+00 5.783560e-01 148 1 29 -3.000000e+00 -2.000000e+00 5.797451e-01 153 1 30 -3.000000e+00 -2.000000e+00 5.807700e-01 158 1 31 -1.000000e+00 -2.000000e+00 5.824389e-01 163 1 32 -1.000000e+00 -2.000000e+00 5.833790e-01 168 1 33 -1.000000e+00 -2.000000e+00 5.844381e-01 173 1 34 -3.000000e+00 -2.000000e+00 5.857790e-01 178 1 35 -1.000000e+00 -2.000000e+00 5.867460e-01 183 1 36 -3.000000e+00 -2.000000e+00 5.878639e-01 188 1 37 -1.000000e+00 -2.000000e+00 5.896780e-01 193 1 38 -1.000000e+00 -2.000000e+00 5.911350e-01 198 1 39 -1.000000e+00 -2.000000e+00 5.922799e-01 203 1 40 -1.000000e+00 -2.000000e+00 5.940230e-01 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.940230e-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, 2017-26 ------------------------------------------------------------------- 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 7.475080e-01 51 1 25 1.560330e+02 2.260386e+02 1.780094e+00 4203 1 30 2.138334e+03 2.336430e+02 3.461740e+00 7674 1 38 8.025312e+02 2.352957e+02 4.659879e+00 10194 1 46 1.737622e+02 2.358930e+02 5.698133e+00 12054 1 58 4.114170e+01 2.360915e+02 6.736405e+00 13734 1 63 1.493193e+03 2.362190e+02 8.284204e+00 15909 1 72 1.044387e+02 2.362973e+02 9.337948e+00 17364 1 100 4.969839e+02 2.364135e+02 1.308907e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.308907e+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, 2017-26 ------------------------------------------------------------------- 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 1.319949e+00 1400 1 20 -4.764789e+00 -4.394789e+00 1.511074e+00 2800 1 30 -4.672487e+00 -4.377000e+00 1.713166e+00 4200 1 40 -4.483495e+00 -4.370632e+00 1.931339e+00 5600 1 50 -4.167321e+00 -4.364999e+00 2.139175e+00 7000 1 60 -4.362455e+00 -4.358864e+00 2.357944e+00 8400 1 70 -4.849916e+00 -4.355337e+00 2.582098e+00 9800 1 80 -4.861568e+00 -4.353006e+00 2.811885e+00 11200 1 90 -4.268264e+00 -4.350407e+00 3.043460e+00 12600 1 100 -4.539897e+00 -4.348641e+00 3.280803e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.280803e+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, 2017-26 ------------------------------------------------------------------- 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 1.204913e+00 1050 1 20 -1.529197e+00 -1.471817e+00 1.258767e+00 1600 1 30 -1.410768e+00 -1.471408e+00 1.375901e+00 2650 1 40 -1.596461e+00 -1.471258e+00 1.434642e+00 3200 1 50 -1.002277e+00 -1.471216e+00 1.557289e+00 4250 1 60 -1.085156e+00 -1.471164e+00 1.620087e+00 4800 1 70 -1.391746e+00 -1.471164e+00 1.763009e+00 5850 1 80 -1.448703e+00 -1.471132e+00 1.831591e+00 6400 1 90 -1.488989e+00 -1.471087e+00 1.965731e+00 7450 1 100 -1.564260e+00 -1.471075e+00 2.038634e+00 8000 1 110 -1.738157e+00 -1.471075e+00 2.108815e+00 8550 1 120 -1.591292e+00 -1.471075e+00 2.180137e+00 9100 1 130 -1.271481e+00 -1.471075e+00 2.250668e+00 9650 1 140 -1.249746e+00 -1.471075e+00 2.328882e+00 10200 1 150 -1.536222e+00 -1.471075e+00 2.410605e+00 10750 1 160 -1.565422e+00 -1.471075e+00 2.497656e+00 11300 1 170 -1.631076e+00 -1.471075e+00 2.580730e+00 11850 1 180 -1.494909e+00 -1.471075e+00 2.665374e+00 12400 1 182 -9.083563e-01 -1.471075e+00 2.683902e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.683902e+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, 2017-26 ------------------------------------------------------------------- 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 4.514289e-01 54 1 20 3.336455e+05 3.402383e+05 4.608529e-01 104 1 30 3.993519e+05 3.403155e+05 4.694691e-01 158 1 40 3.337559e+05 3.403155e+05 4.772589e-01 208 1 48 3.337559e+05 3.403155e+05 4.843380e-01 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.843380e-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, 2017-26 ------------------------------------------------------------------- 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 4.214981e-01 92 1 20 4.506600e+05 4.054833e+05 4.362681e-01 172 1 30 3.959476e+05 4.067125e+05 4.486480e-01 264 1 40 4.497721e+05 4.067125e+05 4.601440e-01 344 1 47 3.959476e+05 4.067125e+05 4.717891e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.717891e-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, 2017-26 ------------------------------------------------------------------- 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 5.937789e+00 14 1 40 2.308500e+03 4.074139e+03 6.527970e+00 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.527970e+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, 2017-26 ------------------------------------------------------------------- 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 2.214325e+00 8 1 6L 4.000000e+04 6.250000e+04 3.271445e+00 60 1 16L 6.000000e+04 6.250000e+04 4.420410e+00 140 1 20L 6.000000e+04 6.250000e+04 5.107365e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.107365e+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, 2017-26 ------------------------------------------------------------------- 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 5.647330e-01 8 1 19 9.500000e+04 6.250000e+04 1.589732e+00 164 1 20 4.000000e+04 6.250000e+04 1.637387e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.637387e+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, 2017-26 ------------------------------------------------------------------- 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 1.166831e+00 5 1 10 4.000000e+04 6.250000e+04 1.618679e+00 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.618679e+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, 2017-26 ------------------------------------------------------------------- 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 6.585109e-01 6 1 20L 9.000000e+00 9.000000e+00 7.462790e-01 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.462790e-01 total solves : 123 best bound : 9.000000e+00 simulation ci : 8.850000e+00 ± 2.940000e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_simple.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 2.440477e+00 87 1 10 -1.109375e+01 2.605769e-01 2.448537e+00 142 1 15 3.105797e+00 5.434132e-01 2.456770e+00 197 1 20 -2.463349e+01 1.503415e+00 2.465595e+00 252 1 25 -1.421085e-14 1.514085e+00 2.474222e+00 307 1 30 4.864000e+01 1.514085e+00 3.915958e+00 394 1 35 4.864000e+01 1.514085e+00 3.924132e+00 449 1 40 -8.870299e+00 1.514085e+00 3.933367e+00 504 1 45 -1.428571e+00 1.514085e+00 3.942436e+00 559 1 48 -1.428571e+00 1.514085e+00 3.948508e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.948508e+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, 2017-26 ------------------------------------------------------------------- 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 1.971350e+00 278 1 20 1.440356e+01 1.278425e+00 1.996532e+00 428 1 30 8.388546e+00 1.278425e+00 2.038825e+00 706 1 40 6.666667e-03 1.278410e+00 2.065880e+00 856 1 50 -5.614035e+00 1.278410e+00 2.109987e+00 1134 1 60 1.426676e+01 1.278410e+00 2.140607e+00 1284 1 64 1.261296e+01 1.278410e+00 2.153777e+00 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.153777e+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, 2017-26 ------------------------------------------------------------------- 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 1.284126e+00 278 1 20 1.111084e+01 1.278410e+00 1.316220e+00 428 1 30 2.293779e+01 1.278410e+00 1.369684e+00 706 1 40 1.426676e+01 1.278410e+00 1.419681e+00 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.419681e+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, 2017-26 ------------------------------------------------------------------- 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 2.694235e+00 1.060052e+01 5.106014e+00 900 1 20 5.498088e+00 1.456766e+01 5.432521e+00 1720 1 30 2.912197e+01 1.665921e+01 6.167722e+00 3036 1 40 1.608515e+01 1.792397e+01 6.973170e+00 4192 1 50 3.997965e+00 1.830624e+01 7.747236e+00 5020 1 60 1.102045e+01 1.840685e+01 8.538113e+00 5808 1 70 8.045596e+00 1.846781e+01 9.350082e+00 6540 1 80 4.710242e+01 1.851858e+01 9.947349e+00 7088 1 90 3.901806e+01 1.865685e+01 1.133588e+01 8180 1 100 8.003646e+00 1.869095e+01 1.198723e+01 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.198723e+01 total solves : 8664 best bound : 1.869095e+01 simulation ci : 2.075231e+01 ± 4.077473e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: biobjective_hydro.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 2.774011e+00 36 1 10 0.000000e+00 0.000000e+00 2.803977e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.803977e+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, 2017-26 ------------------------------------------------------------------- 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 4.693031e-03 407 1 10 2.850000e+02 5.728212e+02 4.474592e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.474592e-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, 2017-26 ------------------------------------------------------------------- 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 4.664898e-03 778 1 10 2.825000e+02 3.465177e+02 4.576397e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.576397e-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, 2017-26 ------------------------------------------------------------------- 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 4.843950e-03 1149 1 10 2.587500e+02 2.052799e+02 4.498911e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.498911e-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, 2017-26 ------------------------------------------------------------------- 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 5.321026e-03 1520 1 10 2.875000e+02 4.661908e+02 5.025697e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.025697e-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, 2017-26 ------------------------------------------------------------------- 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 4.952192e-03 1891 1 10 1.000000e+02 1.129771e+02 4.350400e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.350400e-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, 2017-26 ------------------------------------------------------------------- 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 5.234003e-03 2262 1 10 1.625000e+02 2.794553e+02 4.924512e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.924512e-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, 2017-26 ------------------------------------------------------------------- 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 5.480051e-03 2633 1 10 5.487500e+02 4.077574e+02 5.169606e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.169606e-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, 2017-26 ------------------------------------------------------------------- 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 5.934954e-03 3004 1 10 6.771875e+02 5.210100e+02 1.222210e-01 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.222210e-01 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, 2017-26 ------------------------------------------------------------------- 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 5.361080e-03 3375 1 10 5.312500e+01 5.938345e+01 4.542112e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.542112e-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, 2017-26 ------------------------------------------------------------------- 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 1.792007e+00 235 1 10 1.000000e+01 9.159200e+00 2.143991e+00 310 1 15 1.000000e+01 9.159200e+00 2.536612e+00 385 1 20 1.000000e+01 9.159200e+00 2.908963e+00 460 1 25 1.000000e+01 9.159200e+00 4.970028e+00 695 1 30 4.000000e+00 9.159200e+00 5.329967e+00 770 1 35 1.000000e+01 9.159200e+00 5.692972e+00 845 1 40 1.000000e+01 9.159200e+00 6.087603e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.087603e+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, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 2.16000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [18, 18] AffExpr in MOI.EqualTo{Float64} : [4, 4] AffExpr in MOI.GreaterThan{Float64} : [4, 4] AffExpr in MOI.LessThan{Float64} : [12, 12] VariableRef in MOI.GreaterThan{Float64} : [9, 10] VariableRef in MOI.LessThan{Float64} : [10, 10] VariableRef in MOI.ZeroOne : [9, 9] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+00, 2e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.000000e+00 6.959189e+00 1.520793e+00 510 1 20 1.000000e+01 6.834387e+00 2.781822e+00 720 1 30 7.000000e+00 6.834387e+00 5.723853e+00 1230 1 40 1.000000e+01 6.823805e+00 6.969882e+00 1440 1 50 3.000000e+00 6.823805e+00 9.990826e+00 1950 1 60 2.000000e+00 6.823805e+00 1.124348e+01 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.124348e+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, 2017-26 ------------------------------------------------------------------- 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 8.993424e+00 920 1 20 6.049875e+06 2.075240e+06 1.095165e+01 1340 1 30 5.496647e+05 2.078257e+06 1.853827e+01 2260 1 40 3.985383e+04 2.078257e+06 2.042906e+01 2680 1 50 2.994548e+05 2.078257e+06 2.780673e+01 3600 1 60 3.799457e+06 2.078257e+06 2.971966e+01 4020 1 61 3.549665e+06 2.078257e+06 2.989868e+01 4062 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.989868e+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, 2017-26 ------------------------------------------------------------------- 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 2.239208e+01 920 1 20L 2.799668e+06 2.079457e+06 3.663905e+01 1340 1 30L 3.799443e+06 2.079457e+06 5.800806e+01 2260 1 40L 4.299882e+06 2.079457e+06 7.270007e+01 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.270007e+01 total solves : 2680 best bound : 2.079457e+06 simulation ci : 1.602238e+06 ± 4.944385e+05 numeric issues : 0 ------------------------------------------------------------------- [ Info: hydro_valley.jl [ Info: infinite_horizon_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 2.421811e+00 1914 1 200 0.000000e+00 1.191645e+02 2.688178e+00 3840 1 300 7.500000e+01 1.191666e+02 2.964163e+00 5738 1 328 2.500000e+00 1.191667e+02 3.016722e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.016722e+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, 2017-26 ------------------------------------------------------------------- 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 6.376548e-01 2806 1 200 0.000000e+00 1.191666e+02 9.584768e-01 4749 1 287 5.000000e+00 1.191667e+02 1.193771e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.193771e+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, 2017-26 ------------------------------------------------------------------- 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 3.459580e-01 1033 1 20 8.000000e+00 2.000000e+01 3.640661e-01 1209 1 30 1.200000e+01 2.000000e+01 4.437740e-01 2304 1 40 3.000000e+01 2.000000e+01 5.014071e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.014071e-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, 2017-26 ------------------------------------------------------------------- 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 6.789598e-01 35 1 10 7.500000e+02 2.935390e+03 7.210269e-01 350 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.210269e-01 total solves : 350 best bound : 2.935390e+03 simulation ci : 1.544902e+03 ± 5.533339e+02 numeric issues : 0 ------------------------------------------------------------------- Building and solving inner model for upper bounds: Node: 3 - elapsed time: 0.31 plus 0.47 for vertex selection. Node: 2 - elapsed time: 0.28 plus 0.01 for vertex selection. Node: 1 - elapsed time: 0.47 plus 0.16 for vertex selection. First-stage upper bound: 2969.680973503913 Total time for upper bound: 1.705458611 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, 2017-26 ------------------------------------------------------------------- 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 1.883979e-01 3 1 40 2.000000e+00 2.000000e+00 3.182409e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.182409e-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, 2017-26 ------------------------------------------------------------------- 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 1.202927e+00 1350 1 20 5.062500e+00 4.110713e+00 1.342838e+00 2700 1 30 4.500000e+00 4.104200e+00 1.489807e+00 4050 1 40 3.812500e+00 4.102669e+00 1.640855e+00 5400 1 50 4.725000e+00 4.095504e+00 1.799863e+00 6750 1 60 4.050000e+00 4.092999e+00 1.956287e+00 8100 1 70 4.606250e+00 4.091524e+00 2.114830e+00 9450 1 80 3.875000e+00 4.089694e+00 2.638606e+00 10800 1 90 3.750000e+00 4.089490e+00 2.831244e+00 12150 1 100 5.125000e+00 4.087894e+00 3.024202e+00 13500 1 110 4.500000e+00 4.087478e+00 3.197117e+00 14850 1 120 3.650000e+00 4.086704e+00 3.402903e+00 16200 1 130 4.406250e+00 4.086063e+00 3.584601e+00 17550 1 140 3.375000e+00 4.085981e+00 3.758102e+00 18900 1 150 3.000000e+00 4.085945e+00 3.943096e+00 20250 1 160 3.812500e+00 4.085838e+00 4.187871e+00 21600 1 170 4.250000e+00 4.085728e+00 4.393537e+00 22950 1 180 3.243750e+00 4.085593e+00 4.594398e+00 24300 1 190 4.306250e+00 4.085487e+00 4.786252e+00 25650 1 200 5.237500e+00 4.085446e+00 5.000745e+00 27000 1 210 4.500000e+00 4.085441e+00 5.198184e+00 28350 1 220 3.612500e+00 4.085405e+00 5.403471e+00 29700 1 230 3.700000e+00 4.085382e+00 5.611806e+00 31050 1 240 3.437500e+00 4.085254e+00 5.815522e+00 32400 1 250 4.100000e+00 4.085115e+00 6.018357e+00 33750 1 260 3.000000e+00 4.084973e+00 6.255187e+00 35100 1 270 4.918750e+00 4.084943e+00 6.516112e+00 36450 1 280 2.756250e+00 4.084920e+00 6.829728e+00 37800 1 290 3.737500e+00 4.084868e+00 7.143449e+00 39150 1 300 5.750000e+00 4.084868e+00 7.463369e+00 40500 1 310 5.156250e+00 4.084858e+00 7.780089e+00 41850 1 320 3.131250e+00 4.084855e+00 7.993315e+00 43200 1 330 4.125000e+00 4.084846e+00 8.207419e+00 44550 1 340 5.875000e+00 4.084820e+00 8.430785e+00 45900 1 350 4.587500e+00 4.084810e+00 8.721903e+00 47250 1 360 5.087500e+00 4.084805e+00 8.952327e+00 48600 1 370 4.393750e+00 4.084802e+00 9.173477e+00 49950 1 380 4.750000e+00 4.084792e+00 9.392605e+00 51300 1 390 4.437500e+00 4.084785e+00 9.611202e+00 52650 1 400 4.181250e+00 4.084785e+00 9.829633e+00 54000 1 410 3.650000e+00 4.084777e+00 1.005833e+01 55350 1 420 3.750000e+00 4.084769e+00 1.029086e+01 56700 1 430 3.725000e+00 4.084762e+00 1.051737e+01 58050 1 440 4.218750e+00 4.084751e+00 1.074568e+01 59400 1 450 5.500000e+00 4.084751e+00 1.097453e+01 60750 1 460 3.637500e+00 4.084747e+00 1.119986e+01 62100 1 470 2.993750e+00 4.084743e+00 1.143169e+01 63450 1 480 5.237500e+00 4.084743e+00 1.167948e+01 64800 1 490 4.212500e+00 4.084743e+00 1.190522e+01 66150 1 500 3.843750e+00 4.084743e+00 1.213281e+01 67500 1 510 3.425000e+00 4.084743e+00 1.235530e+01 68850 1 520 4.293750e+00 4.084743e+00 1.257411e+01 70200 1 530 2.818750e+00 4.084740e+00 1.281373e+01 71550 1 540 4.668750e+00 4.084740e+00 1.304508e+01 72900 1 550 2.750000e+00 4.084740e+00 1.328196e+01 74250 1 560 4.100000e+00 4.084740e+00 1.352878e+01 75600 1 570 3.200000e+00 4.084738e+00 1.377631e+01 76950 1 580 3.525000e+00 4.084738e+00 1.401703e+01 78300 1 590 3.125000e+00 4.084738e+00 1.425410e+01 79650 1 600 4.875000e+00 4.084736e+00 1.453738e+01 81000 1 610 4.050000e+00 4.084736e+00 1.477844e+01 82350 1 620 4.750000e+00 4.084733e+00 1.503626e+01 83700 1 630 3.687500e+00 4.084733e+00 1.532623e+01 85050 1 640 3.875000e+00 4.084733e+00 1.557931e+01 86400 1 650 3.625000e+00 4.084733e+00 1.582011e+01 87750 1 660 3.500000e+00 4.084732e+00 1.607524e+01 89100 1 670 4.875000e+00 4.084732e+00 1.633387e+01 90450 1 680 3.925000e+00 4.084732e+00 1.657084e+01 91800 1 690 3.900000e+00 4.084732e+00 1.680946e+01 93150 1 700 4.812500e+00 4.084732e+00 1.706237e+01 94500 1 710 5.625000e+00 4.084732e+00 1.732152e+01 95850 1 720 4.556250e+00 4.084732e+00 1.758528e+01 97200 1 730 5.150000e+00 4.084732e+00 1.784679e+01 98550 1 740 4.275000e+00 4.084732e+00 1.810641e+01 99900 1 750 4.381250e+00 4.084732e+00 1.836770e+01 101250 1 760 4.406250e+00 4.084732e+00 1.863751e+01 102600 1 770 3.393750e+00 4.084732e+00 1.890391e+01 103950 1 780 4.000000e+00 4.084732e+00 1.919498e+01 105300 1 790 3.125000e+00 4.084732e+00 1.947422e+01 106650 1 800 3.500000e+00 4.084732e+00 1.975296e+01 108000 1 810 3.750000e+00 4.084732e+00 2.002524e+01 109350 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.002524e+01 total solves : 109350 best bound : 4.084732e+00 simulation ci : 4.063341e+00 ± 5.176214e-02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.862500e+00 6.435922e+00 6.777802e-01 1350 1 20 3.500000e+00 5.106264e+00 1.237105e+00 2700 1 30 4.181250e+00 5.034558e+00 1.890074e+00 4050 1 40 2.812500e+00 4.734605e+00 2.750503e+00 5400 1 50 4.112500e+00 4.729788e+00 3.776375e+00 6750 1 60 3.500000e+00 4.044267e+00 4.862125e+00 8100 1 70 3.350000e+00 4.042467e+00 6.084226e+00 9450 1 80 3.812500e+00 4.041839e+00 7.557682e+00 10800 1 90 3.618750e+00 4.041612e+00 9.073930e+00 12150 1 100 5.162500e+00 4.041461e+00 1.085496e+01 13500 1 110 4.250000e+00 4.041357e+00 1.270333e+01 14850 1 120 4.500000e+00 4.040834e+00 1.479408e+01 16200 1 130 4.968750e+00 4.040822e+00 1.711543e+01 17550 1 140 5.575000e+00 4.040795e+00 1.949719e+01 18900 1 143 4.125000e+00 4.040795e+00 2.022895e+01 19305 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.022895e+01 total solves : 19305 best bound : 4.040795e+00 simulation ci : 4.042788e+00 ± 1.185303e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_one.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-26 ------------------------------------------------------------------- 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 1.417226e+01 1680 1 20 2.078810e+00 1.166281e+00 1.527114e+01 2560 1 30 3.973033e+00 1.166907e+00 1.648528e+01 3440 1 40 3.706337e+00 1.167312e+00 2.797793e+01 5120 1 50 3.158565e+00 1.167416e+00 2.914405e+01 6000 1 60 3.642642e+00 1.167416e+00 4.062870e+01 7680 1 70 3.451253e+00 1.167416e+00 4.179898e+01 8560 1 71 2.984727e+00 1.167416e+00 4.189345e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.189345e+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, 2017-26 ------------------------------------------------------------------- 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 8.969321e-01 78 1 20 -4.000000e+01 -5.809615e+01 1.443936e+00 148 1 30 -4.000000e+01 -5.809615e+01 2.076944e+00 226 1 40 -4.700000e+01 -5.809615e+01 2.650985e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.650985e+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, 2017-26 ------------------------------------------------------------------- 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 9.944830e-01 138 1 20 -4.000000e+01 -6.196125e+01 1.575473e+00 258 1 30 -7.500000e+01 -6.196125e+01 2.331501e+00 396 1 40 -4.000000e+01 -6.196125e+01 2.873490e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.873490e+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, 2017-26 ------------------------------------------------------------------- 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 1.345312e+00 462 1 20 -5.600000e+01 -6.546793e+01 1.881332e+00 852 1 30 -4.000000e+01 -6.546793e+01 3.463326e+00 1314 1 40 -4.000000e+01 -6.546793e+01 4.014323e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.014323e+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, 2017-26 ------------------------------------------------------------------- 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 1.154204e+00 11 1 9L 1.200000e+01 8.000000e+00 2.264838e+00 180 1 16L 1.200000e+01 8.000000e+00 3.389856e+00 257 1 21L 1.200000e+01 8.000000e+00 4.673804e+00 393 1 28L 1.200000e+01 8.000000e+00 5.741820e+00 470 1 35L 1.200000e+01 8.000000e+00 6.890832e+00 547 1 40L 6.000000e+00 8.000000e+00 7.682964e+00 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.682964e+00 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, 2017-26 ------------------------------------------------------------------- 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 8.681080e-01 6 1 40 1.093500e+05 1.083900e+05 9.212430e-01 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.212430e-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 Total Time SDDP.jl | 2457 2457 36m58.8s Testing SDDP tests passed Testing completed after 2228.39s PkgEval succeeded after 2381.18s