Package evaluation of SDDP on Julia 1.13.0-DEV.464 (abc56fde89*) started at 2025-05-01T20:08:54.509 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... ┌ Warning: could not download https://pkg.julialang.org/registries │ exception = RequestError: HTTP/2 301 (Connection timed out after 30006 milliseconds) while requesting https://pkg.julialang.org/registries └ @ Pkg.Registry /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Registry/Registry.jl:77 Set-up completed after 6.4s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [f4570300] + SDDP v1.11.0 Updating `~/.julia/environments/v1.13/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 v0.18.22 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.4 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v1.0.1 [cd3eb016] + HTTP v1.10.16 [92d709cd] + IrrationalConstants v0.2.4 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [0f8b85d8] + JSON3 v1.14.2 [4076af6c] + JuMP v1.25.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.1.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.39.0 [739be429] + MbedTLS v1.1.9 [d8a4904e] + MutableArithmetics v1.6.4 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.4.3 [bac558e1] + OrderedCollections v1.8.0 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.2 [21216c6a] + Preferences v1.4.3 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.11.0 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.5.1 [1e83bf80] + StaticArraysCore v1.4.3 [10745b16] + Statistics v1.11.1 [856f2bd8] + StructTypes v1.11.0 [a759f4b9] + TimerOutputs v0.5.28 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.5.2 [6e34b625] + Bzip2_jll v1.0.9+0 [c8ffd9c3] + MbedTLS_jll v2.28.6+2 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.12.0 [f489334b] + StyledStrings v1.11.0 [fa267f1f] + TOML v1.0.3 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [14a3606d] + MozillaCACerts_jll v2024.12.31 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.0.16+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.12.0+0 Installation completed after 2.94s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... 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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 Precompiling packages... 26241.3 ms ✓ HiGHS 1 dependency successfully precompiled in 27 seconds. 52 already precompiled. [ 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/EWTpZ/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 2.293110e-01 4 1 3 0.000000e+00 0.000000e+00 5.334921e-01 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.334921e-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 1.418591e-02 9 1 20 7.500000e+04 1.075000e+05 4.422770e-01 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.422770e-01 total solves : 204 best bound : 1.075000e+05 simulation ci : 8.268750e+04 ± 1.084410e+04 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/EWTpZ/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/EWTpZ/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/EWTpZ/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 7.426569e-01 12 1 10 2.500000e+00 3.361111e+01 7.571809e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.571809e-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 7.627964e-03 12 1 10 2.500000e+00 3.361111e+01 1.931000e-02 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.931000e-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 6.430864e-03 46 1 50 0.000000e+00 1.191663e+02 2.759690e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.759690e-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 6.031990e-03 46 1 50 0.000000e+00 1.191663e+02 2.804940e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.804940e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: duality_handlers.jl Precompiling packages... 23568.5 ms ✓ Ipopt → IpoptMathOptInterfaceExt 1 dependency successfully precompiled in 24 seconds. 73 already precompiled. ------------------------------------------------------------------- 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 2.679384e+00 103 1 3S -5.785826e+01 -6.755367e+01 4.069195e+00 309 1 8S -5.772300e+01 -6.677661e+01 5.276581e+00 824 1 13S -3.268889e+01 -6.677644e+01 6.497086e+00 1339 1 19S -4.168889e+01 -6.677644e+01 7.798863e+00 1957 1 25S -4.168889e+01 -6.677644e+01 9.054388e+00 2575 1 49S -6.068889e+01 -6.677644e+01 1.417911e+01 5047 1 73S -7.168889e+01 -6.677644e+01 1.929771e+01 7519 1 97S -6.068889e+01 -6.677644e+01 2.449351e+01 9991 1 100 -8.368889e+01 -6.677644e+01 2.492758e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.492758e+01 total solves : 10300 best bound : -6.677644e+01 simulation ci : -5.960112e+01 ± 3.154656e+00 numeric issues : 0 ------------------------------------------------------------------- ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit https://github.com/coin-or/Ipopt ****************************************************************************** [ Info: forward_passes.jl ┌ 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/EWTpZ/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 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+00 6.000000e+00 2.248679e+02 2 4 20 5.000000e+00 6.000000e+00 2.289062e+02 40 4 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.289062e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 5.800000e+00 ± 1.041026e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/EWTpZ/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 1.844769e-01 48 1 20 9.000000e+00 6.000000e+00 3.423889e-01 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.423889e-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/EWTpZ/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/EWTpZ/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/EWTpZ/src/plugins/risk_measures.jl:528 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 5.829096e-03 4 1 50 0.000000e+00 0.000000e+00 1.765821e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 1.765821e-01 total solves : 200 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/EWTpZ/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/EWTpZ/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/EWTpZ/src/plugins/stopping_rules.jl:132 [ Info: threaded.jl [ Info: value_functions.jl [ Info: visualization.jl Precompiling packages... 3704.9 ms ✓ StatsBase 6744.5 ms ✓ RecipesPipeline 98086.7 ms ✓ Plots 18487.7 ms ✓ Plots → UnitfulExt 4 dependencies successfully precompiled in 128 seconds. 178 already precompiled. ┌ Warning: `SDDP.save` is deprecated. Use `SDDP.plot` instead. │ caller = test_SpaghettiPlot() at visualization.jl:51 └ @ Core ~/.julia/packages/SDDP/EWTpZ/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 6.239842e+00 5 1 20 0.000000e+00 -1.000000e+01 6.709308e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.709308e+00 total solves : 104 best bound : -1.000000e+01 simulation ci : -1.100000e+01 ± 4.474009e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: FAST_production_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -5.320000e+00 -2.396000e+01 1.229787e-02 52 1 10 -2.396000e+01 -2.396000e+01 1.601100e-02 92 1 15 -4.260000e+01 -2.396000e+01 1.999402e-02 132 1 20 -2.396000e+01 -2.396000e+01 2.432680e-02 172 1 25 -5.320000e+00 -2.396000e+01 2.984500e-02 224 1 30 -5.320000e+00 -2.396000e+01 3.492689e-02 264 1 35 -2.396000e+01 -2.396000e+01 4.040289e-02 304 1 40 -2.396000e+01 -2.396000e+01 4.629993e-02 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.629993e-02 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 3.20s / 1.2% 64.8MiB / 12.2% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 24.0ms 60.1% 601μs 5.86MiB 74.4% 150KiB solve_subproblem 160 12.1ms 30.3% 75.7μs 934KiB 11.6% 5.84KiB get_dual_solution 160 657μs 1.6% 4.10μs 190KiB 2.4% 1.19KiB prepare_backward_pass 160 26.5μs 0.1% 166ns 0.00B 0.0% 0.00B forward_pass 40 11.0ms 27.4% 274μs 1.74MiB 22.1% 44.5KiB solve_subproblem 120 10.1ms 25.3% 84.3μs 1.56MiB 19.8% 13.3KiB get_dual_solution 120 46.7μs 0.1% 389ns 13.1KiB 0.2% 112B sample_scenario 40 147μs 0.4% 3.66μs 24.2KiB 0.3% 620B calculate_bound 40 4.96ms 12.4% 124μs 281KiB 3.5% 7.02KiB get_dual_solution 40 20.4μs 0.1% 511ns 4.38KiB 0.1% 112B get_dual_solution 36 13.3μs 0.0% 369ns 3.94KiB 0.0% 112B ──────────────────────────────────────────────────────────────────────────────────── ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -2.396000e+01 -2.396000e+01 3.343797e-02 52 1 10 -2.396000e+01 -2.396000e+01 3.771591e-02 92 1 15 -2.396000e+01 -2.396000e+01 4.268980e-02 132 1 20 -4.260000e+01 -2.396000e+01 4.842687e-02 172 1 25 -5.320000e+00 -2.396000e+01 5.593300e-02 224 1 30 -2.396000e+01 -2.396000e+01 6.370497e-02 264 1 35 -2.396000e+01 -2.396000e+01 7.196879e-02 304 1 40 -5.320000e+00 -2.396000e+01 8.102393e-02 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.102393e-02 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 85.1ms / 88.0% 15.1MiB / 94.0% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 57.8ms 77.2% 1.45ms 12.1MiB 85.7% 311KiB solve_subproblem 160 12.9ms 17.2% 80.6μs 940KiB 6.5% 5.88KiB get_dual_solution 160 670μs 0.9% 4.18μs 190KiB 1.3% 1.19KiB prepare_backward_pass 160 27.6μs 0.0% 173ns 0.00B 0.0% 0.00B forward_pass 40 11.2ms 15.0% 280μs 1.74MiB 12.3% 44.5KiB solve_subproblem 120 10.3ms 13.8% 86.1μs 1.56MiB 11.0% 13.3KiB get_dual_solution 120 42.8μs 0.1% 357ns 13.1KiB 0.1% 112B sample_scenario 40 149μs 0.2% 3.73μs 24.3KiB 0.2% 623B calculate_bound 40 5.82ms 7.8% 145μs 291KiB 2.0% 7.27KiB get_dual_solution 40 36.3μs 0.0% 907ns 4.38KiB 0.0% 112B get_dual_solution 36 13.1μs 0.0% 364ns 3.94KiB 0.0% 112B ──────────────────────────────────────────────────────────────────────────────────── [ Info: FAST_quickstart.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 4] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 5e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 -2.500000e+00 1.761310e-01 5 1 2 -2.500000e+00 -2.000000e+00 1.772399e-01 14 1 3 -1.000000e+00 -2.000000e+00 1.777039e-01 19 1 4 -1.000000e+00 -2.000000e+00 1.781020e-01 24 1 5 -1.000000e+00 -2.000000e+00 1.785040e-01 29 1 6 -3.000000e+00 -2.000000e+00 1.788759e-01 34 1 7 -1.000000e+00 -2.000000e+00 1.792741e-01 39 1 8 -1.000000e+00 -2.000000e+00 1.796601e-01 44 1 9 -3.000000e+00 -2.000000e+00 1.800489e-01 49 1 10 -1.000000e+00 -2.000000e+00 1.804640e-01 54 1 11 -3.000000e+00 -2.000000e+00 1.808710e-01 59 1 12 -3.000000e+00 -2.000000e+00 1.813099e-01 64 1 13 -1.000000e+00 -2.000000e+00 1.817279e-01 69 1 14 -1.000000e+00 -2.000000e+00 1.821620e-01 74 1 15 -3.000000e+00 -2.000000e+00 1.825969e-01 79 1 16 -1.000000e+00 -2.000000e+00 1.830320e-01 84 1 17 -3.000000e+00 -2.000000e+00 1.834879e-01 89 1 18 -3.000000e+00 -2.000000e+00 1.839409e-01 94 1 19 -1.000000e+00 -2.000000e+00 1.844089e-01 99 1 20 -3.000000e+00 -2.000000e+00 1.848741e-01 104 1 21 -1.000000e+00 -2.000000e+00 1.856971e-01 113 1 22 -1.000000e+00 -2.000000e+00 1.861870e-01 118 1 23 -3.000000e+00 -2.000000e+00 1.866760e-01 123 1 24 -3.000000e+00 -2.000000e+00 1.871719e-01 128 1 25 -1.000000e+00 -2.000000e+00 1.876740e-01 133 1 26 -3.000000e+00 -2.000000e+00 1.881881e-01 138 1 27 -3.000000e+00 -2.000000e+00 1.890459e-01 143 1 28 -1.000000e+00 -2.000000e+00 1.895931e-01 148 1 29 -3.000000e+00 -2.000000e+00 1.901200e-01 153 1 30 -3.000000e+00 -2.000000e+00 1.906679e-01 158 1 31 -1.000000e+00 -2.000000e+00 1.912239e-01 163 1 32 -1.000000e+00 -2.000000e+00 1.917789e-01 168 1 33 -1.000000e+00 -2.000000e+00 1.923819e-01 173 1 34 -3.000000e+00 -2.000000e+00 1.929879e-01 178 1 35 -1.000000e+00 -2.000000e+00 1.935780e-01 183 1 36 -3.000000e+00 -2.000000e+00 1.941760e-01 188 1 37 -1.000000e+00 -2.000000e+00 1.947849e-01 193 1 38 -1.000000e+00 -2.000000e+00 1.954160e-01 198 1 39 -1.000000e+00 -2.000000e+00 1.960399e-01 203 1 40 -1.000000e+00 -2.000000e+00 1.966760e-01 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.966760e-01 total solves : 208 best bound : -2.000000e+00 simulation ci : -1.812500e+00 ± 3.171441e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: Hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+00] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.000000e+01 1.882708e+01 1.698680e-01 51 1 30 2.138334e+03 2.336430e+02 1.238982e+00 7674 1 47 3.025787e+02 2.359215e+02 2.280194e+00 12321 1 63 1.493193e+03 2.362190e+02 3.554747e+00 15909 1 75 6.724519e+02 2.363362e+02 4.570114e+00 18477 1 91 1.500190e+02 2.363927e+02 5.579356e+00 21177 1 99 4.184450e+02 2.364095e+02 6.618377e+00 23469 1 100 4.969839e+02 2.364135e+02 6.838095e+00 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.838095e+00 total solves : 23928 best bound : 2.364135e+02 simulation ci : 2.345669e+02 ± 6.032770e+01 numeric issues : 0 ------------------------------------------------------------------- On average, 2.1 units of thermal are used in the first stage. [ Info: StochDynamicProgramming.jl_multistock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 3 scenarios : 1.43489e+07 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [13, 13] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 5e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.977586e+00 -4.446713e+00 5.710242e-01 1400 1 20 -4.764789e+00 -4.394789e+00 7.299051e-01 2800 1 30 -4.672487e+00 -4.377000e+00 8.936882e-01 4200 1 40 -4.483495e+00 -4.370632e+00 1.066341e+00 5600 1 50 -4.167321e+00 -4.364999e+00 1.258434e+00 7000 1 60 -4.362455e+00 -4.358864e+00 1.430323e+00 8400 1 70 -4.849916e+00 -4.355337e+00 1.601208e+00 9800 1 80 -4.861568e+00 -4.353006e+00 1.783462e+00 11200 1 90 -4.268264e+00 -4.350407e+00 1.968452e+00 12600 1 100 -4.539897e+00 -4.348641e+00 2.155248e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.155248e+00 total solves : 14000 best bound : -4.348641e+00 simulation ci : -4.325071e+00 ± 8.068858e-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 2.798898e-01 1050 1 20 -1.529197e+00 -1.471817e+00 3.229499e-01 1600 1 30 -1.410768e+00 -1.471408e+00 4.172270e-01 2650 1 40 -1.596461e+00 -1.471258e+00 4.623978e-01 3200 1 50 -1.002277e+00 -1.471216e+00 5.609159e-01 4250 1 60 -1.085156e+00 -1.471164e+00 6.110549e-01 4800 1 70 -1.391746e+00 -1.471164e+00 7.141099e-01 5850 1 80 -1.448703e+00 -1.471132e+00 7.644038e-01 6400 1 90 -1.488989e+00 -1.471087e+00 8.663979e-01 7450 1 100 -1.564260e+00 -1.471075e+00 9.208338e-01 8000 1 110 -1.738157e+00 -1.471075e+00 9.721038e-01 8550 1 120 -1.591292e+00 -1.471075e+00 1.028705e+00 9100 1 130 -1.271481e+00 -1.471075e+00 1.083713e+00 9650 1 140 -1.249746e+00 -1.471075e+00 1.139090e+00 10200 1 150 -1.536222e+00 -1.471075e+00 1.196157e+00 10750 1 160 -1.565422e+00 -1.471075e+00 1.259793e+00 11300 1 170 -1.631076e+00 -1.471075e+00 1.324010e+00 11850 1 180 -1.494909e+00 -1.471075e+00 1.405272e+00 12400 1 182 -9.083563e-01 -1.471075e+00 1.419864e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.419864e+00 total solves : 12510 best bound : -1.471075e+00 simulation ci : -1.462065e+00 ± 2.699238e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_2stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 4 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+06] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.455904e+05 3.147347e+05 1.360393e-02 54 1 20 3.336455e+05 3.402383e+05 2.090907e-02 104 1 30 3.993519e+05 3.403155e+05 2.728701e-02 158 1 40 3.337559e+05 3.403155e+05 3.253198e-02 208 1 48 3.337559e+05 3.403155e+05 3.740811e-02 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.740811e-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 1.881814e-02 92 1 20 4.506600e+05 4.054833e+05 3.045702e-02 172 1 30 3.959476e+05 4.067125e+05 4.065204e-02 264 1 40 4.497721e+05 4.067125e+05 4.984617e-02 344 1 47 3.959476e+05 4.067125e+05 5.717206e-02 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.717206e-02 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 3.052319e+00 14 1 40 2.308500e+03 4.074139e+03 3.437456e+00 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.437456e+00 total solves : 776 best bound : 4.074139e+03 simulation ci : 4.224313e+03 ± 6.692189e+02 numeric issues : 0 ------------------------------------------------------------------- [ Info: air_conditioning.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 7.000000e+04 6.250000e+04 1.448444e+00 8 1 20L 6.000000e+04 6.250000e+04 2.212696e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.212696e+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 8.471012e-03 8 1 20 4.000000e+04 6.250000e+04 3.297000e-01 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.297000e-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 3.185797e-02 5 1 10 4.000000e+04 6.250000e+04 2.965560e-01 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.965560e-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 2.339280e-01 6 1 20L 9.000000e+00 9.000000e+00 2.976210e-01 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.976210e-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 6.686571e-01 87 1 10 -1.109375e+01 2.605769e-01 6.741731e-01 142 1 15 3.105797e+00 5.434132e-01 6.801929e-01 197 1 20 -2.463349e+01 1.503415e+00 6.868579e-01 252 1 25 -1.421085e-14 1.514085e+00 6.931741e-01 307 1 30 4.864000e+01 1.514085e+00 1.943334e+00 394 1 35 4.864000e+01 1.514085e+00 1.949574e+00 449 1 40 -8.870299e+00 1.514085e+00 1.956413e+00 504 1 45 -1.428571e+00 1.514085e+00 1.963955e+00 559 1 48 -1.428571e+00 1.514085e+00 1.969215e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.969215e+00 total solves : 592 best bound : 1.514085e+00 simulation ci : 2.494033e+00 ± 5.472486e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_stagewise.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.395796e+01 1.428818e+00 5.831590e-01 278 1 20 1.440356e+01 1.278425e+00 6.016240e-01 428 1 30 8.388546e+00 1.278425e+00 6.340590e-01 706 1 40 6.666667e-03 1.278410e+00 6.539030e-01 856 1 50 -5.614035e+00 1.278410e+00 6.860468e-01 1134 1 60 1.426676e+01 1.278410e+00 7.078660e-01 1284 1 64 1.261296e+01 1.278410e+00 7.172568e-01 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.172568e-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 : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.111809e+00 1.278488e+00 4.419184e-02 278 1 20 1.111084e+01 1.278410e+00 6.975794e-02 428 1 30 2.293779e+01 1.278410e+00 1.118269e-01 706 1 40 1.426676e+01 1.278410e+00 1.516290e-01 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.516290e-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 3.538498e+00 900 1 20 6.374753e+00 1.361934e+01 3.689367e+00 1720 1 30 2.848217e+01 1.624016e+01 4.007752e+00 3036 1 40 1.973944e+01 1.776547e+01 4.386916e+00 4192 1 50 4.000000e+00 1.889360e+01 4.735556e+00 5020 1 60 1.143524e+01 1.907862e+01 5.112909e+00 5808 1 70 9.386174e+00 1.961343e+01 5.505831e+00 6540 1 80 5.667808e+01 1.890971e+01 5.754936e+00 7088 1 90 3.740638e+01 1.993168e+01 6.315077e+00 8180 1 100 9.867073e+00 2.001710e+01 6.583826e+00 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.583826e+00 total solves : 8664 best bound : 2.001710e+01 simulation ci : 2.301353e+01 ± 4.670835e+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 1.649278e+00 36 1 10 0.000000e+00 0.000000e+00 1.667266e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.667266e+00 total solves : 360 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 7] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.500000e+02 5.500000e+02 3.169060e-03 407 1 10 2.850000e+02 5.728212e+02 2.994895e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.994895e-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 3.172874e-03 778 1 10 2.825000e+02 3.465177e+02 3.090191e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.090191e-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, 19] 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 2.006818e+02 3.151894e-03 1149 1 10 2.587500e+02 2.052799e+02 2.889705e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.889705e-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 3.929853e-03 1520 1 10 2.875000e+02 4.661908e+02 3.403783e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.403783e-02 total solves : 1844 best bound : 4.661908e+02 simulation ci : 5.075000e+02 ± 1.503394e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 30] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.112500e+02 1.129545e+02 3.154039e-03 1891 1 10 1.000000e+02 1.129771e+02 2.703094e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.703094e-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 3.213882e-03 2262 1 10 1.625000e+02 2.794553e+02 3.171897e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.171897e-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, 38] 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 3.721952e-03 2633 1 10 5.487500e+02 4.077574e+02 3.423309e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.423309e-02 total solves : 2957 best bound : 4.077574e+02 simulation ci : 3.863418e+02 ± 9.936379e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 43] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.718750e+02 5.198033e+02 3.870964e-03 3004 1 10 6.771875e+02 5.210100e+02 3.484797e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.484797e-02 total solves : 3328 best bound : 5.210100e+02 simulation ci : 5.831217e+02 ± 1.295425e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 50] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.812500e+01 5.720558e+01 3.221989e-03 3375 1 10 5.312500e+01 5.938345e+01 2.750897e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 2.750897e-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 6.323519e-01 235 1 10 1.000000e+01 9.159200e+00 7.742050e-01 310 1 15 1.000000e+01 9.159200e+00 9.191990e-01 385 1 20 1.000000e+01 9.159200e+00 1.092400e+00 460 1 25 1.000000e+01 9.159200e+00 1.905236e+00 695 1 30 4.000000e+00 9.159200e+00 2.057336e+00 770 1 35 1.000000e+01 9.159200e+00 2.191376e+00 845 1 40 1.000000e+01 9.159200e+00 2.360219e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.360219e+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 4.205039e-01 510 1 20 1.000000e+01 6.834387e+00 8.885460e-01 720 1 30 7.000000e+00 6.834387e+00 2.017520e+00 1230 1 40 1.000000e+01 6.823805e+00 2.498499e+00 1440 1 50 3.000000e+00 6.823805e+00 3.662562e+00 1950 1 60 2.000000e+00 6.823805e+00 4.209510e+00 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.209510e+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 5.706581e+00 920 1 20 6.049875e+06 2.075240e+06 7.466535e+00 1340 1 30 5.496647e+05 2.078257e+06 1.333351e+01 2260 1 40 3.985383e+04 2.078257e+06 1.505159e+01 2680 1 50 2.994548e+05 2.078257e+06 2.081452e+01 3600 1 60 3.799457e+06 2.078257e+06 2.262586e+01 4020 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.262586e+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 1.168403e+01 920 1 20L 3.984407e+04 2.079401e+06 1.998784e+01 1340 1 30L 5.495606e+05 2.079457e+06 3.201689e+01 2260 1 40L 3.799861e+06 2.079457e+06 4.036862e+01 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.036862e+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 1.188534e+02 1.997909e+00 1914 1 200 0.000000e+00 1.191645e+02 2.318964e+00 3840 1 300 7.500000e+01 1.191666e+02 2.629483e+00 5738 1 328 2.500000e+00 1.191667e+02 2.692956e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.692956e+00 total solves : 6034 best bound : 1.191667e+02 simulation ci : 2.272866e+01 ± 3.596240e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 128.14 ± 13.91 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.191232e+02 4.340940e-01 2806 1 200 0.000000e+00 1.191666e+02 9.006660e-01 4749 1 287 5.000000e+00 1.191667e+02 1.151878e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.151878e+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 9.575391e-02 1033 1 20 8.000000e+00 2.000000e+01 1.174018e-01 1209 1 30 1.200000e+01 2.000000e+01 2.193780e-01 2304 1 40 3.000000e+01 2.000000e+01 2.904348e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.904348e-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 4.755020e-03 3 1 40 2.000000e+00 2.000000e+00 7.406282e-02 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.406282e-02 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 6.211421e-01 1350 1 20 5.062500e+00 4.110713e+00 7.495241e-01 2700 1 30 4.500000e+00 4.104200e+00 9.102890e-01 4050 1 40 3.812500e+00 4.102669e+00 1.080619e+00 5400 1 50 4.725000e+00 4.095504e+00 1.252882e+00 6750 1 60 4.050000e+00 4.092999e+00 1.416716e+00 8100 1 70 4.606250e+00 4.091524e+00 1.676934e+00 9450 1 80 3.875000e+00 4.089694e+00 1.851938e+00 10800 1 90 3.750000e+00 4.089490e+00 2.019632e+00 12150 1 100 5.125000e+00 4.087894e+00 2.198544e+00 13500 1 110 4.500000e+00 4.087478e+00 2.392385e+00 14850 1 120 3.650000e+00 4.086704e+00 2.581920e+00 16200 1 130 4.406250e+00 4.086063e+00 2.765595e+00 17550 1 140 3.375000e+00 4.085981e+00 2.941743e+00 18900 1 150 3.000000e+00 4.085945e+00 3.128688e+00 20250 1 160 3.812500e+00 4.085838e+00 3.315581e+00 21600 1 170 4.250000e+00 4.085728e+00 3.505152e+00 22950 1 180 3.243750e+00 4.085593e+00 3.692077e+00 24300 1 190 4.306250e+00 4.085487e+00 3.882048e+00 25650 1 200 5.237500e+00 4.085446e+00 4.082753e+00 27000 1 210 4.500000e+00 4.085441e+00 4.282473e+00 28350 1 220 3.612500e+00 4.085405e+00 4.495281e+00 29700 1 230 3.700000e+00 4.085382e+00 4.727214e+00 31050 1 240 3.437500e+00 4.085254e+00 4.948024e+00 32400 1 250 4.100000e+00 4.085115e+00 5.173500e+00 33750 1 260 3.000000e+00 4.084973e+00 5.410471e+00 35100 1 270 4.918750e+00 4.084943e+00 5.626903e+00 36450 1 280 2.756250e+00 4.084920e+00 5.884059e+00 37800 1 290 3.737500e+00 4.084868e+00 6.143693e+00 39150 1 300 5.750000e+00 4.084868e+00 6.389627e+00 40500 1 310 5.156250e+00 4.084858e+00 6.686956e+00 41850 1 320 3.131250e+00 4.084855e+00 6.901815e+00 43200 1 330 4.125000e+00 4.084846e+00 7.123287e+00 44550 1 340 5.875000e+00 4.084820e+00 7.343294e+00 45900 1 350 4.587500e+00 4.084810e+00 7.570570e+00 47250 1 360 5.087500e+00 4.084805e+00 7.839004e+00 48600 1 370 4.393750e+00 4.084802e+00 8.097585e+00 49950 1 380 4.750000e+00 4.084792e+00 8.366899e+00 51300 1 390 4.437500e+00 4.084785e+00 8.627193e+00 52650 1 400 4.181250e+00 4.084785e+00 8.902796e+00 54000 1 410 3.650000e+00 4.084777e+00 9.148887e+00 55350 1 420 3.750000e+00 4.084769e+00 9.392807e+00 56700 1 430 3.725000e+00 4.084762e+00 9.640444e+00 58050 1 440 4.218750e+00 4.084751e+00 9.909919e+00 59400 1 450 5.500000e+00 4.084751e+00 1.018519e+01 60750 1 460 3.637500e+00 4.084747e+00 1.045030e+01 62100 1 470 2.993750e+00 4.084743e+00 1.069702e+01 63450 1 480 5.237500e+00 4.084743e+00 1.097454e+01 64800 1 490 4.212500e+00 4.084743e+00 1.125036e+01 66150 1 500 3.843750e+00 4.084743e+00 1.151737e+01 67500 1 510 3.425000e+00 4.084743e+00 1.179019e+01 68850 1 520 4.293750e+00 4.084743e+00 1.205338e+01 70200 1 530 2.818750e+00 4.084740e+00 1.234492e+01 71550 1 540 4.668750e+00 4.084740e+00 1.265945e+01 72900 1 550 2.750000e+00 4.084740e+00 1.293811e+01 74250 1 560 4.100000e+00 4.084740e+00 1.323874e+01 75600 1 570 3.200000e+00 4.084738e+00 1.353445e+01 76950 1 580 3.525000e+00 4.084738e+00 1.381159e+01 78300 1 590 3.125000e+00 4.084738e+00 1.407689e+01 79650 1 600 4.875000e+00 4.084736e+00 1.437820e+01 81000 1 610 4.050000e+00 4.084736e+00 1.465331e+01 82350 1 620 4.750000e+00 4.084733e+00 1.494744e+01 83700 1 630 3.687500e+00 4.084733e+00 1.522677e+01 85050 1 640 3.875000e+00 4.084733e+00 1.552679e+01 86400 1 650 3.625000e+00 4.084733e+00 1.580657e+01 87750 1 660 3.500000e+00 4.084732e+00 1.611720e+01 89100 1 670 4.875000e+00 4.084732e+00 1.642393e+01 90450 1 680 3.925000e+00 4.084732e+00 1.668997e+01 91800 1 690 3.900000e+00 4.084732e+00 1.696766e+01 93150 1 700 4.812500e+00 4.084732e+00 1.725908e+01 94500 1 710 5.625000e+00 4.084732e+00 1.756925e+01 95850 1 720 4.556250e+00 4.084732e+00 1.788405e+01 97200 1 730 5.150000e+00 4.084732e+00 1.819813e+01 98550 1 740 4.275000e+00 4.084732e+00 1.851242e+01 99900 1 750 4.381250e+00 4.084732e+00 1.882759e+01 101250 1 760 4.406250e+00 4.084732e+00 1.919011e+01 102600 1 770 3.393750e+00 4.084732e+00 1.948811e+01 103950 1 780 4.000000e+00 4.084732e+00 1.980408e+01 105300 1 787 4.125000e+00 4.084732e+00 2.002352e+01 106245 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.002352e+01 total solves : 106245 best bound : 4.084732e+00 simulation ci : 4.069909e+00 ± 5.263221e-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 5.425000e+00 4.057673e+00 3.383780e-01 1350 1 20 5.250000e+00 4.052229e+00 9.751251e-01 2700 1 30 3.825000e+00 4.048981e+00 1.910824e+00 4050 1 40 4.750000e+00 4.047875e+00 3.201821e+00 5400 1 50 3.625000e+00 4.047393e+00 4.541544e+00 6750 1 60 3.875000e+00 4.046612e+00 6.108868e+00 8100 1 70 4.406250e+00 4.044066e+00 7.836651e+00 9450 1 80 3.875000e+00 4.039387e+00 9.644918e+00 10800 1 90 4.418750e+00 4.038996e+00 1.171027e+01 12150 1 100 3.906250e+00 4.038943e+00 1.382620e+01 13500 1 110 4.537500e+00 4.038880e+00 1.615296e+01 14850 1 120 5.125000e+00 4.038863e+00 1.977000e+01 16200 1 121 5.006250e+00 4.038863e+00 2.002783e+01 16335 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.002783e+01 total solves : 16335 best bound : 4.038863e+00 simulation ci : 4.079203e+00 ± 1.229451e-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 4.811618e+00 1680 1 20 2.078810e+00 1.166281e+00 5.322873e+00 2560 1 30 3.973033e+00 1.166907e+00 5.868184e+00 3440 1 40 3.706337e+00 1.167312e+00 1.063510e+01 5120 1 50 3.158565e+00 1.167416e+00 1.117625e+01 6000 1 60 3.642642e+00 1.167416e+00 1.601200e+01 7680 1 70 3.451253e+00 1.167416e+00 1.656034e+01 8560 1 71 2.984727e+00 1.167416e+00 1.660288e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.660288e+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 3.131509e-01 78 1 20 -4.000000e+01 -5.809615e+01 6.554151e-01 148 1 30 -4.000000e+01 -5.809615e+01 1.030463e+00 226 1 40 -4.700000e+01 -5.809615e+01 1.359197e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.359197e+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 3.330951e-01 138 1 20 -4.000000e+01 -6.196125e+01 6.849370e-01 258 1 30 -7.500000e+01 -6.196125e+01 1.169001e+00 396 1 40 -4.000000e+01 -6.196125e+01 1.496039e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.496039e+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 5.414510e-01 462 1 20 -5.600000e+01 -6.546793e+01 9.553890e-01 852 1 30 -4.000000e+01 -6.546793e+01 2.042441e+00 1314 1 40 -4.000000e+01 -6.546793e+01 2.424510e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.424510e+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 4.404731e-01 11 1 14L 6.000000e+00 8.000000e+00 1.496390e+00 235 1 25L 6.000000e+00 8.000000e+00 2.524422e+00 437 1 37L 6.000000e+00 8.000000e+00 3.525355e+00 569 1 40L 6.000000e+00 8.000000e+00 3.756418e+00 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.756418e+00 total solves : 602 best bound : 8.000000e+00 simulation ci : 8.475000e+00 ± 8.904404e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: the_farmers_problem.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 3 scenarios : 3.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 19] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 16] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 2e+01] objective range [1e+00, 1e+03] bounds range [6e+03, 5e+05] rhs range [2e+02, 5e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -9.800000e+04 4.922260e+05 4.679449e-01 6 1 40 1.093500e+05 1.083900e+05 4.942329e-01 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.942329e-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 | 2399 2399 24m04.0s Testing SDDP tests passed Testing completed after 1450.27s PkgEval succeeded after 1624.75s