Package evaluation of SDDP on Julia 1.10.8 (92f03a4775*) started at 2025-02-25T10:07:47.090 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 5.1s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Installed SDDP ─ v1.10.4 Updating `~/.julia/environments/v1.10/Project.toml` [f4570300] + SDDP v1.10.4 Updating `~/.julia/environments/v1.10/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.0 [d1d4a3ce] + BitFlags v0.1.9 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.16.0 [f0e56b4a] + ConcurrentUtilities v2.5.0 [864edb3b] + DataStructures v0.18.20 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.3 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v0.10.38 [cd3eb016] + HTTP v1.10.15 [92d709cd] + IrrationalConstants v0.2.4 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [0f8b85d8] + JSON3 v1.14.1 [4076af6c] + JuMP v1.24.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.1.0 [1914dd2f] + MacroTools v0.5.15 [b8f27783] + MathOptInterface v1.37.0 [739be429] + MbedTLS v1.1.9 [d8a4904e] + MutableArithmetics v1.6.4 [77ba4419] + NaNMath v1.1.2 [4d8831e6] + OpenSSL v1.4.3 [bac558e1] + OrderedCollections v1.8.0 [69de0a69] + Parsers v2.8.1 [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.10.4 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.5.0 [1e83bf80] + StaticArraysCore v1.4.3 [856f2bd8] + StructTypes v1.11.0 [a759f4b9] + TimerOutputs v0.5.27 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.5.1 [6e34b625] + Bzip2_jll v1.0.9+0 [458c3c95] + OpenSSL_jll v3.0.16+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [56f22d72] + Artifacts [2a0f44e3] + Base64 [ade2ca70] + Dates [8ba89e20] + Distributed [b77e0a4c] + InteractiveUtils [76f85450] + LibGit2 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [de0858da] + Printf [9abbd945] + Profile [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [05823500] + OpenLibm_jll v0.8.1+4 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 Installation completed after 7.8s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 31.75s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_FE7VmR/Project.toml` [cd3eb016] HTTP v1.10.15 [87dc4568] HiGHS v1.13.0 [682c06a0] JSON v0.21.4 [7d188eb4] JSONSchema v1.4.1 [4076af6c] JuMP v1.24.0 [d8a4904e] MutableArithmetics v1.6.4 [91a5bcdd] Plots v1.40.9 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [f4570300] SDDP v1.10.4 [a759f4b9] TimerOutputs v0.5.27 [8ba89e20] Distributed [f43a241f] Downloads v1.6.0 [37e2e46d] LinearAlgebra [44cfe95a] Pkg v1.10.0 [de0858da] Printf [9a3f8284] Random [ea8e919c] SHA v0.7.0 [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_FE7VmR/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [6e4b80f9] BenchmarkTools v1.6.0 [d1d4a3ce] BitFlags v0.1.9 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.29.0 [3da002f7] ColorTypes v0.12.0 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.0 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Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... [ Info: Experimental.jl [ Info: fetching remote ref https://jump.dev/MathOptFormat/schemas/mof.1.schema.json [ Info: MSPFormat.jl [ Info: algorithm.jl ┌ Warning: Unable to recover in direct mode! Remove `direct = true` when creating the policy graph. └ @ SDDP ~/.julia/packages/SDDP/mqTVN/src/algorithm.jl:391 [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.AffExpr in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [2, 2] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- † 1 0.000000e+00 0.000000e+00 3.019218e-01 4 1 3 0.000000e+00 0.000000e+00 6.481609e-01 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.481609e-01 total solves : 12 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 1 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [4, 4] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.100000e+05 1.075000e+05 5.733609e-02 9 1 20 7.500000e+04 1.075000e+05 5.605621e-01 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.605621e-01 total solves : 204 best bound : 1.075000e+05 simulation ci : 8.250000e+04 ± 1.093364e+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/mqTVN/src/algorithm.jl:1170 ┌ 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/mqTVN/src/algorithm.jl:1170 [ 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/mqTVN/src/modeling_aids.jl:125 [ Info: user_interface.jl [ Info: backward_sampling_schemes.jl [ Info: bellman_functions.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.138889e+01 8.653240e-01 12 1 10 2.500000e+00 3.361111e+01 8.917630e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.917630e-01 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 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 6.848097e-03 12 1 10 2.500000e+00 3.361111e+01 2.701807e-02 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.701807e-02 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 1.066589e-02 46 1 50 0.000000e+00 1.191663e+02 4.787090e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.787090e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 1.077199e-02 46 1 50 0.000000e+00 1.191663e+02 5.016911e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.016911e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: duality_handlers.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 1.00000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 11] JuMP.AffExpr in MOI.LessThan{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [3, 7] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 7] JuMP.VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -4.650000e+01 -7.053967e+01 3.005218e+00 103 1 3S -5.785826e+01 -6.755367e+01 4.303394e+00 309 1 8S -5.772300e+01 -6.677661e+01 5.543323e+00 824 1 13S -3.268889e+01 -6.677644e+01 6.844786e+00 1339 1 19S -4.168889e+01 -6.677644e+01 8.195971e+00 1957 1 25S -4.168889e+01 -6.677644e+01 9.488844e+00 2575 1 49S -6.068889e+01 -6.677644e+01 1.477573e+01 5047 1 73S -7.168889e+01 -6.677644e+01 2.000241e+01 7519 1 97S -6.068889e+01 -6.677644e+01 2.526677e+01 9991 1 100 -8.368889e+01 -6.677644e+01 2.574485e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.574485e+01 total solves : 10300 best bound : -6.677644e+01 simulation ci : -5.960112e+01 ± 3.154656e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: forward_passes.jl ┌ 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/mqTVN/src/algorithm.jl:1170 [ 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 Activating new project at `~/.julia/packages/SDDP/mqTVN/test` From worker 3: Activating new project at `~/.julia/packages/SDDP/mqTVN/test` From worker 5: Activating new project at `~/.julia/packages/SDDP/mqTVN/test` From worker 2: Activating new project at `~/.julia/packages/SDDP/mqTVN/test` From worker 4: Activating new project at `~/.julia/packages/SDDP/mqTVN/test` ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.000000e+00 6.000000e+00 2.090659e+02 2 5 20 7.000000e+00 6.000000e+00 2.120962e+02 40 3 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.120962e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 6.400000e+00 ± 9.474815e-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/mqTVN/src/algorithm.jl:1170 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : true options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [4e+00, 4e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 5.000000e+00 6.000000e+00 5.127771e-01 48 1 20 9.000000e+00 6.000000e+00 8.713660e-01 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.713660e-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/mqTVN/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/mqTVN/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/mqTVN/src/plugins/risk_measures.jl:528 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 4.321098e-03 4 1 50 0.000000e+00 0.000000e+00 5.447602e-02 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 5.447602e-02 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/mqTVN/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/mqTVN/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/mqTVN/src/plugins/stopping_rules.jl:132 [ 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:51 └ @ Main.TestVisualization ~/.julia/packages/SDDP/mqTVN/test/visualization/visualization.jl:51 [ Info: FAST_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+00] bounds range [8e+00, 8e+00] rhs range [6e+00, 6e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -2.000000e+01 -1.000000e+01 4.164910e-02 5 1 20 0.000000e+00 -1.000000e+01 6.166506e-02 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.166506e-02 total solves : 104 best bound : -1.000000e+01 simulation ci : -1.100000e+01 ± 4.474009e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: FAST_production_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -5.320000e+00 -2.396000e+01 1.379204e-02 52 1 10 -2.396000e+01 -2.396000e+01 2.097797e-02 92 1 15 -4.260000e+01 -2.396000e+01 2.847004e-02 132 1 20 -2.396000e+01 -2.396000e+01 3.736997e-02 172 1 25 -5.320000e+00 -2.396000e+01 9.677100e-02 224 1 30 -5.320000e+00 -2.396000e+01 1.063900e-01 264 1 35 -2.396000e+01 -2.396000e+01 1.167901e-01 304 1 40 -2.396000e+01 -2.396000e+01 1.278429e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.278429e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 2.48s / 4.8% 9.54MiB / 76.7% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 93.4ms 78.1% 2.33ms 6.14MiB 84.0% 157KiB solve_subproblem 160 23.1ms 19.3% 144μs 976KiB 13.0% 6.10KiB get_dual_solution 160 1.11ms 0.9% 6.96μs 212KiB 2.8% 1.33KiB prepare_backward_pass 160 84.0μs 0.1% 525ns 0.00B 0.0% 0.00B forward_pass 40 15.5ms 13.0% 387μs 914KiB 12.2% 22.9KiB solve_subproblem 120 13.1ms 11.0% 109μs 703KiB 9.4% 5.86KiB get_dual_solution 120 145μs 0.1% 1.21μs 65.6KiB 0.9% 560B sample_scenario 40 511μs 0.4% 12.8μs 36.7KiB 0.5% 940B calculate_bound 40 10.6ms 8.9% 265μs 266KiB 3.6% 6.66KiB get_dual_solution 40 56.1μs 0.0% 1.40μs 21.9KiB 0.3% 560B get_dual_solution 36 42.0μs 0.0% 1.17μs 19.7KiB 0.3% 560B ──────────────────────────────────────────────────────────────────────────────────── ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -2.396000e+01 -2.396000e+01 1.401401e-02 52 1 10 -2.396000e+01 -2.396000e+01 2.163506e-02 92 1 15 -2.396000e+01 -2.396000e+01 3.091693e-02 132 1 20 -4.260000e+01 -2.396000e+01 4.135108e-02 172 1 25 -5.320000e+00 -2.396000e+01 5.530500e-02 224 1 30 -2.396000e+01 -2.396000e+01 6.916595e-02 264 1 35 -2.396000e+01 -2.396000e+01 8.537102e-02 304 1 40 -5.320000e+00 -2.396000e+01 1.044161e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.044161e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 110ms / 87.0% 14.2MiB / 94.5% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 67.0ms 69.8% 1.67ms 12.3MiB 91.3% 314KiB solve_subproblem 160 24.9ms 25.9% 155μs 0.95MiB 7.1% 6.11KiB get_dual_solution 160 1.16ms 1.2% 7.26μs 212KiB 1.5% 1.33KiB prepare_backward_pass 160 113μs 0.1% 706ns 0.00B 0.0% 0.00B forward_pass 40 16.2ms 16.9% 405μs 914KiB 6.6% 22.9KiB solve_subproblem 120 13.5ms 14.1% 112μs 703KiB 5.1% 5.86KiB get_dual_solution 120 122μs 0.1% 1.01μs 65.6KiB 0.5% 560B sample_scenario 40 536μs 0.6% 13.4μs 36.8KiB 0.3% 943B calculate_bound 40 12.7ms 13.2% 317μs 268KiB 1.9% 6.70KiB get_dual_solution 40 62.3μs 0.1% 1.56μs 21.9KiB 0.2% 560B get_dual_solution 36 37.1μs 0.0% 1.03μs 19.7KiB 0.1% 560B ──────────────────────────────────────────────────────────────────────────────────── [ Info: FAST_quickstart.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 4] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 5e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 -2.500000e+00 4.322052e-03 5 1 2 -2.500000e+00 -2.000000e+00 5.959988e-03 14 1 3 -1.000000e+00 -2.000000e+00 6.678104e-03 19 1 4 -1.000000e+00 -2.000000e+00 7.591009e-03 24 1 5 -2.000000e+00 -2.000000e+00 8.522987e-03 29 1 6 -2.000000e+00 -2.000000e+00 9.392977e-03 34 1 7 -2.000000e+00 -2.000000e+00 1.028609e-02 39 1 8 -2.000000e+00 -2.000000e+00 1.116204e-02 44 1 9 -2.000000e+00 -2.000000e+00 1.208305e-02 49 1 10 -2.000000e+00 -2.000000e+00 1.302314e-02 54 1 11 -2.000000e+00 -2.000000e+00 1.399803e-02 59 1 12 -2.000000e+00 -2.000000e+00 1.495004e-02 64 1 13 -2.000000e+00 -2.000000e+00 1.594019e-02 69 1 14 -2.000000e+00 -2.000000e+00 1.693106e-02 74 1 15 -2.000000e+00 -2.000000e+00 1.793098e-02 79 1 16 -2.000000e+00 -2.000000e+00 1.896310e-02 84 1 17 -2.000000e+00 -2.000000e+00 1.999998e-02 89 1 18 -2.000000e+00 -2.000000e+00 2.105904e-02 94 1 19 -2.000000e+00 -2.000000e+00 2.210498e-02 99 1 20 -2.000000e+00 -2.000000e+00 2.319908e-02 104 1 21 -2.000000e+00 -2.000000e+00 2.501798e-02 113 1 22 -2.000000e+00 -2.000000e+00 2.621412e-02 118 1 23 -2.000000e+00 -2.000000e+00 2.738500e-02 123 1 24 -2.000000e+00 -2.000000e+00 2.854204e-02 128 1 25 -2.000000e+00 -2.000000e+00 2.973104e-02 133 1 26 -2.000000e+00 -2.000000e+00 3.089213e-02 138 1 27 -2.000000e+00 -2.000000e+00 3.211999e-02 143 1 28 -2.000000e+00 -2.000000e+00 3.335214e-02 148 1 29 -2.000000e+00 -2.000000e+00 3.462601e-02 153 1 30 -2.000000e+00 -2.000000e+00 3.600717e-02 158 1 31 -2.000000e+00 -2.000000e+00 3.723717e-02 163 1 32 -2.000000e+00 -2.000000e+00 3.875208e-02 168 1 33 -2.000000e+00 -2.000000e+00 4.041100e-02 173 1 34 -2.000000e+00 -2.000000e+00 4.192710e-02 178 1 35 -2.000000e+00 -2.000000e+00 4.334712e-02 183 1 36 -2.000000e+00 -2.000000e+00 4.480004e-02 188 1 37 -2.000000e+00 -2.000000e+00 4.621720e-02 193 1 38 -2.000000e+00 -2.000000e+00 4.760504e-02 198 1 39 -2.000000e+00 -2.000000e+00 4.908609e-02 203 1 40 -2.000000e+00 -2.000000e+00 5.062819e-02 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.062819e-02 total solves : 208 best bound : -2.000000e+00 simulation ci : -1.912500e+00 ± 1.209829e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: Hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+00] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.000000e+01 2.084129e+01 1.055269e-01 51 1 25 1.558023e+02 2.264900e+02 1.146912e+00 4203 1 30 2.114637e+03 2.341048e+02 2.449044e+00 7674 1 38 7.971548e+02 2.355555e+02 3.470551e+00 10194 1 47 3.042702e+02 2.360066e+02 4.586083e+00 12321 1 59 3.334107e+02 2.361880e+02 5.668760e+00 14097 1 65 6.869873e+02 2.363121e+02 6.832951e+00 16611 1 76 2.976331e+02 2.363752e+02 8.021351e+00 18936 1 87 1.151068e+02 2.364000e+02 9.079654e+00 20673 1 100 4.975845e+02 2.364188e+02 1.149331e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.149331e+01 total solves : 23928 best bound : 2.364188e+02 simulation ci : 2.334486e+02 ± 5.981472e+01 numeric issues : 0 ------------------------------------------------------------------- On average, 2.2 units of thermal are used in the first stage. [ Info: StochDynamicProgramming.jl_multistock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 3 scenarios : 1.43489e+07 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [13, 13] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 5e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.977586e+00 -4.446713e+00 7.405651e-01 1400 1 20 -4.798922e+00 -4.392912e+00 9.924579e-01 2800 1 30 -4.633686e+00 -4.379213e+00 1.267670e+00 4200 1 40 -4.547694e+00 -4.371269e+00 1.541968e+00 5600 1 50 -4.247864e+00 -4.364505e+00 1.825180e+00 7000 1 60 -4.424879e+00 -4.359785e+00 2.118004e+00 8400 1 70 -4.850363e+00 -4.356377e+00 2.418917e+00 9800 1 80 -4.802062e+00 -4.353790e+00 2.695001e+00 11200 1 90 -4.238845e+00 -4.351441e+00 2.967164e+00 12600 1 100 -4.504339e+00 -4.349169e+00 3.253791e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.253791e+00 total solves : 14000 best bound : -4.349169e+00 simulation ci : -4.321335e+00 ± 8.063366e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StochDynamicProgramming.jl_stock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 1 scenarios : 1.00000e+05 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 2e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -1.671715e+00 -1.476962e+00 1.239610e-01 1050 1 20 -1.529410e+00 -1.471808e+00 1.958909e-01 1600 1 30 -1.412014e+00 -1.471396e+00 4.014559e-01 2650 1 40 -1.596116e+00 -1.471184e+00 4.864569e-01 3200 1 50 -9.989658e-01 -1.471163e+00 6.588039e-01 4250 1 60 -1.085289e+00 -1.471110e+00 7.509780e-01 4800 1 70 -1.391746e+00 -1.471110e+00 9.265730e-01 5850 1 80 -1.448703e+00 -1.471087e+00 1.016473e+00 6400 1 90 -1.488989e+00 -1.471075e+00 1.183232e+00 7450 1 100 -1.564260e+00 -1.471075e+00 1.279338e+00 8000 1 110 -1.738157e+00 -1.471075e+00 1.374296e+00 8550 1 120 -1.591292e+00 -1.471075e+00 1.485474e+00 9100 1 130 -1.271481e+00 -1.471075e+00 1.602468e+00 9650 1 140 -1.249746e+00 -1.471075e+00 1.719874e+00 10200 1 150 -1.536222e+00 -1.471075e+00 1.879141e+00 10750 1 160 -1.565422e+00 -1.471075e+00 1.996596e+00 11300 1 170 -1.631076e+00 -1.471075e+00 2.121436e+00 11850 1 180 -1.494909e+00 -1.471075e+00 2.251031e+00 12400 1 182 -9.083563e-01 -1.471075e+00 2.275574e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.275574e+00 total solves : 12510 best bound : -1.471075e+00 simulation ci : -1.462169e+00 ± 2.699325e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_2stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 4 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+06] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.455904e+05 3.147347e+05 1.501608e-02 54 1 20 3.336455e+05 3.402383e+05 2.689409e-02 104 1 30 3.993519e+05 3.403155e+05 4.334903e-02 158 1 40 3.337559e+05 3.403155e+05 6.030798e-02 208 1 48 3.337559e+05 3.403155e+05 7.494402e-02 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.494402e-02 total solves : 248 best bound : 3.403155e+05 simulation ci : 1.298444e+08 ± 1.785864e+08 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_3stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+05] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.403329e+05 3.509666e+05 2.734494e-02 92 1 20 4.506600e+05 4.054833e+05 4.896903e-02 172 1 30 3.959476e+05 4.067125e+05 7.769990e-02 264 1 40 4.497721e+05 4.067125e+05 1.073880e-01 344 1 47 3.959476e+05 4.067125e+05 1.311450e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.311450e-01 total solves : 400 best bound : 4.067125e+05 simulation ci : 2.696242e+07 ± 3.645299e+07 numeric issues : 0 ------------------------------------------------------------------- [ Info: agriculture_mccardle_farm.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 10 state variables : 4 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [24, 24] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 6] VariableRef in MOI.GreaterThan{Float64} : [20, 20] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 8e+01] objective range [1e+00, 1e+03] bounds range [6e+01, 6e+01] rhs range [2e+02, 3e+03] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 8.316000e+03 0.000000e+00 6.009007e-02 14 1 40 2.308500e+03 4.074139e+03 3.594291e-01 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.594291e-01 total solves : 776 best bound : 4.074139e+03 simulation ci : 4.224313e+03 ± 6.692189e+02 numeric issues : 0 ------------------------------------------------------------------- [ Info: air_conditioning.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.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 9.444709e-01 8 1 20L 6.000000e+04 6.250000e+04 1.773737e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.773737e+00 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.475000e+04 ± 7.336233e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 7.235050e-03 8 1 20 4.000000e+04 6.250000e+04 3.309789e-01 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.309789e-01 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.950000e+04 ± 8.933885e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). [ Info: air_conditioning_forward.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [1e+02, 3e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 6.982017e-02 5 1 10 4.000000e+04 6.250000e+04 2.169001e-01 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.169001e-01 total solves : 50 best bound : 6.250000e+04 simulation ci : 5.450000e+04 ± 1.135842e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 9.000000e+00 8.079815e-02 6 1 20L 9.000000e+00 9.000000e+00 1.639690e-01 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.639690e-01 total solves : 123 best bound : 9.000000e+00 simulation ci : 8.850000e+00 ± 2.940000e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_simple.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -1.109375e+01 2.605769e-01 5.718200e-01 87 1 10 -1.109375e+01 2.605769e-01 5.804410e-01 142 1 15 3.105797e+00 5.434132e-01 5.893650e-01 197 1 20 -2.463349e+01 1.503415e+00 5.988691e-01 252 1 25 0.000000e+00 1.514085e+00 6.093850e-01 307 1 30 4.864000e+01 1.514085e+00 1.602339e+00 394 1 35 4.864000e+01 1.514085e+00 1.631743e+00 449 1 40 -8.870299e+00 1.514085e+00 1.644956e+00 504 1 45 -1.428571e+00 1.514085e+00 1.658591e+00 559 1 48 -1.428571e+00 1.514085e+00 1.667450e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.667450e+00 total solves : 592 best bound : 1.514085e+00 simulation ci : 2.494033e+00 ± 5.472486e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_stagewise.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #160 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.395796e+01 1.428818e+00 5.663390e-01 278 1 20 1.440356e+01 1.278425e+00 6.023481e-01 428 1 30 8.388546e+00 1.278425e+00 6.637490e-01 706 1 40 6.666667e-03 1.278410e+00 7.067661e-01 856 1 50 -5.614035e+00 1.278410e+00 8.171241e-01 1134 1 60 1.426676e+01 1.278410e+00 8.727801e-01 1284 1 64 1.261296e+01 1.278410e+00 8.966091e-01 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.966091e-01 total solves : 1344 best bound : 1.278410e+00 simulation ci : 8.172580e-01 ± 5.385320e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #160 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.111809e+00 1.278488e+00 6.084085e-02 278 1 20 1.111084e+01 1.278410e+00 1.061740e-01 428 1 30 2.293779e+01 1.278410e+00 1.764970e-01 706 1 40 1.426676e+01 1.278410e+00 2.429008e-01 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.429008e-01 total solves : 856 best bound : 1.278410e+00 simulation ci : 3.654300e+00 ± 6.176856e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: belief.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 4 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.787277e+00 9.346930e+00 6.368029e-01 900 1 20 6.374753e+00 1.361934e+01 1.019174e+00 1720 1 30 2.813321e+01 1.651297e+01 1.892142e+00 3036 1 40 1.654759e+01 1.632970e+01 2.938772e+00 4192 1 50 3.570941e+00 1.846889e+01 3.543843e+00 5020 1 60 1.087425e+01 1.890254e+01 4.353754e+00 5808 1 70 9.381610e+00 1.940320e+01 5.232315e+00 6540 1 80 5.648731e+01 1.962435e+01 5.902243e+00 7088 1 90 3.879273e+01 1.981008e+01 7.428731e+00 8180 1 100 7.870187e+00 1.997117e+01 8.127508e+00 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.127508e+00 total solves : 8664 best bound : 1.997117e+01 simulation ci : 2.275399e+01 ± 4.541987e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: biobjective_hydro.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 9.909153e-03 36 1 10 0.000000e+00 0.000000e+00 5.231214e-02 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.231214e-02 total solves : 360 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 7] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.500000e+02 5.500000e+02 6.012917e-03 407 1 10 2.850000e+02 5.728212e+02 5.761790e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.761790e-02 total solves : 731 best bound : 5.728212e+02 simulation ci : 6.480000e+02 ± 1.400040e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 13] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.150000e+02 3.347014e+02 5.142927e-03 778 1 10 2.825000e+02 3.465177e+02 5.578995e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.578995e-02 total solves : 1102 best bound : 3.465177e+02 simulation ci : 3.598954e+02 ± 6.281469e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 20] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.387500e+02 1.994007e+02 5.179882e-03 1149 1 10 2.587500e+02 2.052799e+02 5.944204e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.944204e-02 total solves : 1473 best bound : 2.052799e+02 simulation ci : 2.206923e+02 ± 2.764045e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 24] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.375000e+02 4.637735e+02 6.742001e-03 1520 1 10 2.875000e+02 4.661908e+02 1.055510e-01 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.055510e-01 total solves : 1844 best bound : 4.661908e+02 simulation ci : 5.075000e+02 ± 1.503394e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 30] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.112500e+02 1.129545e+02 5.946159e-03 1891 1 10 1.000000e+02 1.129771e+02 5.959511e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.959511e-02 total solves : 2215 best bound : 1.129771e+02 simulation ci : 1.068750e+02 ± 2.168477e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 34] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.562500e+02 2.788383e+02 8.174181e-03 2262 1 10 1.625000e+02 2.794553e+02 6.636715e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.636715e-02 total solves : 2586 best bound : 2.794553e+02 simulation ci : 2.690625e+02 ± 6.720434e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 37] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.810804e+02 4.073537e+02 6.362915e-03 2633 1 10 5.487500e+02 4.077594e+02 6.322908e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.322908e-02 total solves : 2957 best bound : 4.077594e+02 simulation ci : 3.863418e+02 ± 9.936379e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 44] 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 6.628990e-03 3004 1 10 6.771875e+02 5.210100e+02 6.324005e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.324005e-02 total solves : 3328 best bound : 5.210100e+02 simulation ci : 5.831217e+02 ± 1.295425e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 51] 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 6.045818e-03 3375 1 10 5.312500e+01 5.938345e+01 5.973792e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.973792e-02 total solves : 3699 best bound : 5.938345e+01 simulation ci : 6.187500e+01 ± 1.306667e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: booking_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [10, 10] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.GreaterThan{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 6] VariableRef in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.ZeroOne : [5, 5] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 8.000000e+00 9.440450e+00 7.755220e-01 235 1 10 1.000000e+01 9.159200e+00 9.565420e-01 310 1 15 1.000000e+01 9.159200e+00 1.107551e+00 385 1 20 1.000000e+01 9.159200e+00 1.282125e+00 460 1 25 1.000000e+01 9.159200e+00 2.111540e+00 695 1 30 4.000000e+00 9.159200e+00 2.263056e+00 770 1 35 1.000000e+01 9.159200e+00 2.404568e+00 845 1 40 1.000000e+01 9.159200e+00 2.561586e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.561586e+00 total solves : 920 best bound : 9.159200e+00 simulation ci : 7.200000e+00 ± 8.485598e-01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 2.16000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [18, 18] AffExpr in MOI.EqualTo{Float64} : [4, 4] AffExpr in MOI.GreaterThan{Float64} : [4, 4] AffExpr in MOI.LessThan{Float64} : [12, 12] VariableRef in MOI.EqualTo{Float64} : [4, 4] VariableRef in MOI.GreaterThan{Float64} : [9, 10] VariableRef in MOI.LessThan{Float64} : [10, 10] VariableRef in MOI.ZeroOne : [9, 9] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+00, 2e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.000000e+00 6.959189e+00 4.856322e-01 510 1 20 1.000000e+01 6.834387e+00 9.746070e-01 720 1 30 7.000000e+00 6.834387e+00 2.138596e+00 1230 1 40 1.000000e+01 6.823805e+00 2.636618e+00 1440 1 50 3.000000e+00 6.823805e+00 3.808599e+00 1950 1 60 2.000000e+00 6.823805e+00 4.301665e+00 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.301665e+00 total solves : 2160 best bound : 6.823805e+00 simulation ci : 6.183333e+00 ± 6.694539e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: generation_expansion.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.299676e+06 2.074407e+06 5.694946e+00 920 1 20 6.049875e+06 2.075240e+06 7.407212e+00 1340 1 30 5.496647e+05 2.078257e+06 1.345703e+01 2260 1 40 3.985383e+04 2.078257e+06 1.521007e+01 2680 1 50 2.994548e+05 2.078257e+06 2.095106e+01 3600 1 60 3.799457e+06 2.078257e+06 2.287078e+01 4020 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.287078e+01 total solves : 4020 best bound : 2.078257e+06 simulation ci : 2.419054e+06 ± 5.154891e+05 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10L 1.299572e+06 2.079330e+06 1.166949e+01 920 1 20L 3.984407e+04 2.079401e+06 1.999312e+01 1340 1 30L 5.495606e+05 2.079457e+06 3.198111e+01 2260 1 40L 3.799861e+06 2.079457e+06 4.115776e+01 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.115776e+01 total solves : 2680 best bound : 2.079457e+06 simulation ci : 1.720973e+06 ± 5.166660e+05 numeric issues : 0 ------------------------------------------------------------------- [ Info: hydro_valley.jl [ Info: infinite_horizon_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.188512e+02 1.019672e+00 1914 1 200 0.000000e+00 1.191644e+02 1.429952e+00 3840 1 300 7.500000e+01 1.191666e+02 1.842802e+00 5738 1 328 2.500000e+00 1.191667e+02 1.933058e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.933058e+00 total solves : 6034 best bound : 1.191667e+02 simulation ci : 2.272866e+01 ± 3.596240e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 128.14 ± 13.91 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.191223e+02 5.494559e-01 2806 1 200 0.000000e+00 1.191666e+02 1.083772e+00 4749 1 287 5.000000e+00 1.191667e+02 1.495650e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.495650e+00 total solves : 5662 best bound : 1.191667e+02 simulation ci : 2.112369e+01 ± 3.684376e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 122.02 ± 14.06 [ Info: infinite_horizon_trivial.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 2.000000e+01 1.998872e+01 1.335320e-01 1033 1 20 8.000000e+00 2.000000e+01 1.658940e-01 1209 1 30 1.200000e+01 2.000000e+01 2.874072e-01 2304 1 40 3.000000e+01 2.000000e+01 3.810410e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.810410e-01 total solves : 2594 best bound : 2.000000e+01 simulation ci : 1.970000e+01 ± 4.721453e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: no_strong_duality.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.000000e+00 1.500000e+00 4.284191e-02 3 1 40 2.000000e+00 2.000000e+00 1.274920e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.274920e-01 total solves : 604 best bound : 2.000000e+00 simulation ci : 2.150000e+00 ± 5.038753e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: objective_state_newsvendor.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.675000e+00 4.115510e+00 6.334140e-01 1350 1 20 5.062500e+00 4.110716e+00 7.874870e-01 2700 1 30 4.500000e+00 4.104200e+00 9.623530e-01 4050 1 40 3.812500e+00 4.102665e+00 1.137800e+00 5400 1 50 4.725000e+00 4.095495e+00 1.331135e+00 6750 1 60 4.050000e+00 4.092995e+00 1.538183e+00 8100 1 70 4.600000e+00 4.091535e+00 1.751578e+00 9450 1 80 3.875000e+00 4.089708e+00 2.015079e+00 10800 1 90 3.750000e+00 4.089501e+00 2.219539e+00 12150 1 100 5.125000e+00 4.087892e+00 2.453057e+00 13500 1 110 4.500000e+00 4.087471e+00 2.686460e+00 14850 1 120 3.650000e+00 4.086690e+00 2.920378e+00 16200 1 130 4.406250e+00 4.086063e+00 3.165027e+00 17550 1 140 3.375000e+00 4.085979e+00 3.386900e+00 18900 1 150 3.000000e+00 4.085943e+00 3.634801e+00 20250 1 160 3.781250e+00 4.085835e+00 3.867066e+00 21600 1 170 4.250000e+00 4.085725e+00 4.114643e+00 22950 1 180 3.243750e+00 4.085593e+00 4.358987e+00 24300 1 190 4.306250e+00 4.085487e+00 4.601810e+00 25650 1 200 5.237500e+00 4.085443e+00 4.859890e+00 27000 1 210 4.500000e+00 4.085438e+00 5.115779e+00 28350 1 220 3.612500e+00 4.085397e+00 5.396972e+00 29700 1 230 3.700000e+00 4.085379e+00 5.666055e+00 31050 1 240 3.437500e+00 4.085243e+00 5.919024e+00 32400 1 250 4.100000e+00 4.085110e+00 6.161006e+00 33750 1 260 3.000000e+00 4.084986e+00 6.437529e+00 35100 1 270 4.918750e+00 4.084958e+00 6.695638e+00 36450 1 280 2.756250e+00 4.084931e+00 6.983599e+00 37800 1 290 3.737500e+00 4.084885e+00 7.262424e+00 39150 1 300 5.750000e+00 4.084885e+00 7.548826e+00 40500 1 310 5.156250e+00 4.084871e+00 7.835707e+00 41850 1 320 3.131250e+00 4.084868e+00 8.114842e+00 43200 1 330 4.125000e+00 4.084859e+00 8.400788e+00 44550 1 340 5.875000e+00 4.084833e+00 8.686578e+00 45900 1 350 4.587500e+00 4.084823e+00 8.985669e+00 47250 1 360 5.087500e+00 4.084818e+00 9.286981e+00 48600 1 370 4.393750e+00 4.084814e+00 9.576981e+00 49950 1 380 4.750000e+00 4.084804e+00 9.868737e+00 51300 1 390 4.437500e+00 4.084797e+00 1.016160e+01 52650 1 400 4.181250e+00 4.084796e+00 1.045088e+01 54000 1 410 3.650000e+00 4.084789e+00 1.074948e+01 55350 1 420 3.750000e+00 4.084778e+00 1.105253e+01 56700 1 430 3.725000e+00 4.084769e+00 1.135115e+01 58050 1 440 4.218750e+00 4.084755e+00 1.165499e+01 59400 1 450 5.500000e+00 4.084755e+00 1.195742e+01 60750 1 460 3.637500e+00 4.084751e+00 1.225018e+01 62100 1 470 2.993750e+00 4.084746e+00 1.254072e+01 63450 1 480 5.237500e+00 4.084746e+00 1.284430e+01 64800 1 490 4.237500e+00 4.084746e+00 1.314425e+01 66150 1 500 3.843750e+00 4.084746e+00 1.344672e+01 67500 1 510 3.425000e+00 4.084746e+00 1.375267e+01 68850 1 520 4.293750e+00 4.084746e+00 1.405103e+01 70200 1 530 2.818750e+00 4.084740e+00 1.436117e+01 71550 1 540 4.668750e+00 4.084740e+00 1.466322e+01 72900 1 550 2.750000e+00 4.084740e+00 1.498280e+01 74250 1 560 4.100000e+00 4.084740e+00 1.531324e+01 75600 1 570 3.200000e+00 4.084738e+00 1.565064e+01 76950 1 580 3.525000e+00 4.084738e+00 1.592912e+01 78300 1 590 3.125000e+00 4.084738e+00 1.621103e+01 79650 1 600 4.875000e+00 4.084736e+00 1.650852e+01 81000 1 610 4.050000e+00 4.084736e+00 1.680873e+01 82350 1 620 4.750000e+00 4.084733e+00 1.713653e+01 83700 1 630 3.562500e+00 4.084733e+00 1.742927e+01 85050 1 640 3.875000e+00 4.084733e+00 1.773956e+01 86400 1 650 3.625000e+00 4.084733e+00 1.804429e+01 87750 1 660 3.500000e+00 4.084732e+00 1.835712e+01 89100 1 670 4.875000e+00 4.084732e+00 1.867352e+01 90450 1 680 3.925000e+00 4.084732e+00 1.896819e+01 91800 1 690 3.900000e+00 4.084732e+00 1.927720e+01 93150 1 700 4.812500e+00 4.084732e+00 1.960369e+01 94500 1 710 5.625000e+00 4.084732e+00 1.994582e+01 95850 1 712 4.500000e+00 4.084732e+00 2.000883e+01 96120 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.000883e+01 total solves : 96120 best bound : 4.084732e+00 simulation ci : 4.073350e+00 ± 5.636487e-02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.562500e+00 5.043839e+00 3.784459e-01 1350 1 20 5.625000e+00 4.054343e+00 1.037660e+00 2700 1 30 5.250000e+00 4.041300e+00 2.023709e+00 4050 1 40 3.450000e+00 4.038688e+00 3.149695e+00 5400 1 50 4.575000e+00 4.038448e+00 4.497972e+00 6750 1 60 2.400000e+00 4.038303e+00 6.039001e+00 8100 1 70 4.375000e+00 4.038249e+00 7.925275e+00 9450 1 80 3.375000e+00 4.038247e+00 9.730154e+00 10800 1 90 4.950000e+00 4.038084e+00 1.155758e+01 12150 1 100 3.281250e+00 4.038085e+00 1.384804e+01 13500 1 110 4.500000e+00 4.038014e+00 1.631845e+01 14850 1 120 3.450000e+00 4.038014e+00 1.938391e+01 16200 1 123 3.356250e+00 4.038014e+00 2.017601e+01 16605 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.017601e+01 total solves : 16605 best bound : 4.038014e+00 simulation ci : 4.113110e+00 ± 1.360777e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_one.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 8 state variables : 1 scenarios : 1.00000e+08 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [1, 2] VariableRef in MOI.ZeroOne : [1, 1] numerical stability report matrix range [1e+00, 2e+00] objective range [5e-01, 1e+00] bounds range [1e+00, 1e+00] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.219176e+00 1.165102e+00 5.006218e+00 1680 1 20 2.078810e+00 1.166281e+00 5.544440e+00 2560 1 30 3.973033e+00 1.166907e+00 6.135785e+00 3440 1 40 3.706337e+00 1.167312e+00 1.100461e+01 5120 1 50 3.158565e+00 1.167416e+00 1.157134e+01 6000 1 60 3.642642e+00 1.167416e+00 1.651777e+01 7680 1 70 3.451253e+00 1.167416e+00 1.712266e+01 8560 1 71 2.984727e+00 1.167416e+00 1.717193e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.717193e+01 total solves : 8648 best bound : 1.167416e+00 simulation ci : 3.293853e+00 ± 1.130135e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_two.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.000000e+01 -5.809615e+01 2.962239e-01 78 1 20 -4.000000e+01 -5.809615e+01 6.512430e-01 148 1 30 -4.000000e+01 -5.809615e+01 1.085202e+00 226 1 40 -4.700000e+01 -5.809615e+01 1.445116e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.445116e+00 total solves : 296 best bound : -5.809615e+01 simulation ci : -5.346250e+01 ± 7.152725e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 9.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -6.300000e+01 -6.196125e+01 3.565331e-01 138 1 20 -4.000000e+01 -6.196125e+01 7.225211e-01 258 1 30 -7.500000e+01 -6.196125e+01 1.243486e+00 396 1 40 -4.000000e+01 -6.196125e+01 1.633533e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.633533e+00 total solves : 516 best bound : -6.196125e+01 simulation ci : -6.108750e+01 ± 7.148463e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 3.60000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -7.000000e+01 -6.546793e+01 6.009610e-01 462 1 20 -5.600000e+01 -6.546793e+01 1.007954e+00 852 1 30 -4.000000e+01 -6.546793e+01 2.124925e+00 1314 1 40 -4.000000e+01 -6.546793e+01 2.518641e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.518641e+00 total solves : 1704 best bound : -6.546793e+01 simulation ci : -5.991250e+01 ± 5.174250e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: stochastic_all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 1.200000e+01 4.486530e-01 11 1 15L 6.000000e+00 8.000000e+00 1.489875e+00 246 1 26L 6.000000e+00 8.000000e+00 2.553883e+00 448 1 39L 6.000000e+00 8.000000e+00 3.583867e+00 591 1 40L 6.000000e+00 8.000000e+00 3.656834e+00 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.656834e+00 total solves : 602 best bound : 8.000000e+00 simulation ci : 8.475000e+00 ± 8.904404e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: the_farmers_problem.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 3 scenarios : 3.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 19] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 16] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 2e+01] objective range [1e+00, 1e+03] bounds range [6e+03, 5e+05] rhs range [2e+02, 5e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -9.800000e+04 4.922260e+05 6.179950e-01 6 1 40 1.093500e+05 1.083900e+05 6.932020e-01 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.932020e-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 | 2311 2311 19m38.7s Testing SDDP tests passed Testing completed after 1186.28s PkgEval succeeded after 1263.65s