Package evaluation to test SDDP on Julia 1.12.4 (01a2eadb04*) started at 2026-01-09T05:33:41.387 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 7.69s ################################################################################ # Installation # Installing SDDP... Resolving package versions... Updating `~/.julia/environments/v1.12/Project.toml` [f4570300] + SDDP v1.13.1 Updating `~/.julia/environments/v1.12/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.3 [d1d4a3ce] + BitFlags v0.1.9 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [f0e56b4a] + ConcurrentUtilities v2.5.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [e2ba6199] + ExprTools v0.1.10 [f6369f11] + ForwardDiff v1.3.1 [cd3eb016] + HTTP v1.10.19 [92d709cd] + IrrationalConstants v0.2.6 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.3.0 [0f8b85d8] + JSON3 v1.14.3 [4076af6c] + JuMP v1.29.3 [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.48.0 [739be429] + MbedTLS v1.1.9 [d8a4904e] + MutableArithmetics v1.6.7 [77ba4419] + NaNMath v1.1.3 [4d8831e6] + OpenSSL v1.6.1 [bac558e1] + OrderedCollections v1.8.1 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.1 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [f4570300] + SDDP v1.13.1 [777ac1f9] + SimpleBufferStream v1.2.0 [276daf66] + SpecialFunctions v2.6.1 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [856f2bd8] + StructTypes v1.11.0 [ec057cc2] + StructUtils v2.6.1 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.6.1 [6e34b625] + Bzip2_jll v1.0.9+0 [c8ffd9c3] + MbedTLS_jll v2.28.1010+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [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 v2025.11.4 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [bea87d4a] + SuiteSparse_jll v7.8.3+2 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.15.0+0 Installation completed after 5.14s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Error: Failed to use TestEnv.jl; test dependencies will not be precompiled │ exception = │ UndefVarError: `project_rel_path` not defined in `TestEnv` │ Suggestion: this global was defined as `Pkg.Operations.project_rel_path` but not assigned a value. │ Stacktrace: │ [1] get_test_dir(ctx::Pkg.Types.Context, pkgspec::PackageSpec) │ @ TestEnv ~/.julia/packages/TestEnv/iseFl/src/julia-1.11/common.jl:75 │ [2] test_dir_has_project_file │ @ ~/.julia/packages/TestEnv/iseFl/src/julia-1.11/common.jl:52 [inlined] │ [3] maybe_gen_project_override! │ @ ~/.julia/packages/TestEnv/iseFl/src/julia-1.11/common.jl:83 [inlined] │ [4] activate(pkg::String; allow_reresolve::Bool) │ @ TestEnv ~/.julia/packages/TestEnv/iseFl/src/julia-1.11/activate_set.jl:12 │ [5] activate(pkg::String) │ @ TestEnv ~/.julia/packages/TestEnv/iseFl/src/julia-1.11/activate_set.jl:9 │ [6] top-level scope │ @ /PkgEval.jl/scripts/precompile.jl:24 │ [7] include(mod::Module, _path::String) │ @ Base ./Base.jl:306 │ [8] exec_options(opts::Base.JLOptions) │ @ Base ./client.jl:317 │ [9] _start() │ @ Base ./client.jl:550 └ @ Main /PkgEval.jl/scripts/precompile.jl:26 Precompiling package dependencies... Precompiling packages... 59180.9 ms ✓ SDDP 1 dependency successfully precompiled in 60 seconds. 71 already precompiled. Precompilation completed after 72.71s ################################################################################ # Testing # Testing SDDP Status `/tmp/jl_uVKGVh/Project.toml` [87dc4568] HiGHS v1.20.1 [b6b21f68] Ipopt v1.13.0 [682c06a0] JSON v1.3.0 [7d188eb4] JSONSchema v1.5.0 [91a5bcdd] Plots v1.41.4 [f4570300] SDDP v1.13.1 [10745b16] Statistics v1.11.1 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [44cfe95a] Pkg v1.12.1 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_uVKGVh/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [6e4b80f9] BenchmarkTools v1.6.3 [d1d4a3ce] BitFlags v0.1.9 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.31.0 [3da002f7] ColorTypes v0.12.1 [c3611d14] ColorVectorSpace v0.11.0 [5ae59095] Colors v0.13.1 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [f0e56b4a] ConcurrentUtilities v2.5.0 [d38c429a] Contour v0.6.3 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.19.3 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CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.15.0+0 [e37daf67] LibGit2_jll v1.9.0+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.11.4 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.4+0 [efcefdf7] PCRE2_jll v10.44.0+1 [bea87d4a] SuiteSparse_jll v7.8.3+2 [83775a58] Zlib_jll v1.3.1+2 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.64.0+1 [3f19e933] p7zip_jll v17.7.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... [ Info: Experimental.jl Precompiling packages... 10325.2 ms ✓ MathOptIIS 34845.2 ms ✓ HiGHS 2 dependencies successfully precompiled in 46 seconds. 55 already precompiled. Precompiling packages... 1580.5 ms ✓ JSONSchema 1 dependency successfully precompiled in 2 seconds. 22 already precompiled. Precompiling packages... 1504.4 ms ✓ JSONSchema → JSONSchemaJSON3Ext 1 dependency successfully precompiled in 2 seconds. 26 already precompiled. [ Info: fetching remote ref https://jump.dev/MathOptFormat/schemas/mof.1.schema.json [ Info: Inner.jl Node: 3 - elapsed time: 0.4 plus 11.05 for vertex selection. Node: 2 - elapsed time: 0.32 plus 0.3 for vertex selection. Node: 1 - elapsed time: 0.33 plus 0.29 for vertex selection. First-stage upper bound: 45.83333333333332 Total time for upper bound: 12.69209704 ┌ Warning: You must select an optimizer for performing vertex selection. └ @ SDDP.Inner ~/.julia/packages/SDDP/ScjyB/src/Inner.jl:1048 Node: 19 - elapsed time: 0.38 plus 0.35 for vertex selection. Node: 18 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 17 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 16 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 15 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 14 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 13 - elapsed time: 0.49 plus 0.5 for vertex selection. Node: 12 - elapsed time: 0.47 plus 0.33 for vertex selection. Node: 11 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 10 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 9 - elapsed time: 0.47 plus 0.35 for vertex selection. Node: 8 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 7 - elapsed time: 0.49 plus 0.34 for vertex selection. Node: 6 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 5 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 4 - elapsed time: 0.46 plus 0.34 for vertex selection. Node: 3 - elapsed time: 0.47 plus 0.34 for vertex selection. Node: 2 - elapsed time: 0.48 plus 0.34 for vertex selection. Node: 1 - elapsed time: 0.48 plus 0.33 for vertex selection. Selection removed 500 vertices [ Info: MSPFormat.jl [ Info: algorithm.jl ┌ Warning: Unable to recover in direct mode! Remove `direct = true` when creating the policy graph. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:401 [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` [ Info: Writing cuts to the file `model_infeasible_node_1.cuts.json` ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.AffExpr in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [2, 2] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- † 1 0.000000e+00 0.000000e+00 5.999811e-01 4 1 3 0.000000e+00 0.000000e+00 1.115906e+00 12 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.115906e+00 total solves : 12 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 1 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [4, 4] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.100000e+05 1.075000e+05 4.421921e-01 9 1 20 7.500000e+04 1.075000e+05 1.079170e+00 204 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.079170e+00 total solves : 204 best bound : 1.075000e+05 simulation ci : 8.268750e+04 ± 1.084410e+04 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 [ Info: binary_expansion.jl [ Info: deterministic_equivalent.jl [ Info: modeling_aids.jl ┌ Warning: Budget for nodes is less than the number of stages. Using one node per stage. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/modeling_aids.jl:125 [ Info: user_interface.jl [ Info: backward_sampling_schemes.jl [ Info: bellman_functions.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.138889e+01 1.575030e+00 12 1 10 2.500000e+00 3.361111e+01 1.603700e+00 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.603700e+00 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [2e+00, 1e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.500000e+01 2.083333e+01 4.077580e-01 12 1 10 2.500000e+00 3.361111e+01 4.481251e-01 120 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.481251e-01 total solves : 120 best bound : 3.361111e+01 simulation ci : 2.775000e+01 ± 3.280073e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 9.725094e-03 46 1 50 0.000000e+00 1.191663e+02 4.731810e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.731810e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] JuMP.AffExpr in MOI.EqualTo{Float64} : [2, 2] JuMP.VariableRef in MOI.EqualTo{Float64} : [3, 3] JuMP.VariableRef in MOI.GreaterThan{Float64} : [5, 5] JuMP.VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.250000e+01 5.268631e+01 1.049185e-02 46 1 50 0.000000e+00 1.191663e+02 5.053849e-01 1625 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 5.053849e-01 total solves : 1625 best bound : 1.191663e+02 simulation ci : 7.795000e+01 ± 2.885518e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: duality_handlers.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 1.00000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 11] JuMP.AffExpr in MOI.LessThan{Float64} : [2, 2] JuMP.VariableRef in MOI.GreaterThan{Float64} : [3, 7] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 7] JuMP.VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -4.650000e+01 -7.053967e+01 3.306018e+00 103 1 3S -5.785826e+01 -6.755367e+01 4.920388e+00 309 1 5S -7.577792e+01 -6.680771e+01 6.978208e+00 515 1 6S -6.064080e+01 -6.678327e+01 8.047786e+00 618 1 13S -3.268889e+01 -6.677644e+01 1.343951e+01 1339 1 23S -3.268889e+01 -6.677644e+01 1.883701e+01 2369 1 33S -8.368889e+01 -6.677644e+01 2.483866e+01 3399 1 43S -8.368889e+01 -6.677644e+01 3.065503e+01 4429 1 53S -4.868889e+01 -6.677644e+01 3.667043e+01 5459 1 63S -8.068889e+01 -6.677644e+01 4.213601e+01 6489 1 73S -7.168889e+01 -6.677644e+01 4.749468e+01 7519 1 83S -7.168889e+01 -6.677644e+01 5.328622e+01 8549 1 93S -6.068889e+01 -6.677644e+01 5.867179e+01 9579 1 100 -8.368889e+01 -6.677644e+01 6.198612e+01 10300 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 6.198612e+01 total solves : 10300 best bound : -6.677644e+01 simulation ci : -5.960112e+01 ± 3.154656e+00 numeric issues : 0 ------------------------------------------------------------------- ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit https://github.com/coin-or/Ipopt ****************************************************************************** [ Info: forward_passes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] JuMP.VariableRef in MOI.EqualTo{Float64} : [1, 1] JuMP.VariableRef in MOI.GreaterThan{Float64} : [1, 1] JuMP.VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 3.000000e+00 6.000000e+00 1.002407e-02 8 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.002407e-02 total solves : 8 best bound : 6.000000e+00 simulation ci : 3.000000e+00 ± NaN numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 [ Info: local_improvement_search.jl [ Info: exp = 15 [ Info: OA(exp) = 220 [ Info: piecewise = 7 [ Info: OA(piecewise) = 6 [ Info: squared = 3 [ Info: OA(squared) = 16 [ Info: parallel_schemes.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [1, 1] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.000000e+00 6.000000e+00 2.976371e+02 2 2 20 5.000000e+00 6.000000e+00 3.028049e+02 40 2 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.028049e+02 total solves : 40 best bound : 6.000000e+00 simulation ci : 6.100000e+00 ± 1.043935e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Re-training a model with existing cuts! │ │ Are you sure you want to do this? The output from this training may be │ misleading because the policy is already partially trained. │ │ If you meant to train a new policy with different settings, you must │ build a new model. │ │ If you meant to refine a previously trained policy, turn off this │ warning by passing `add_to_existing_cuts = true` as a keyword argument │ to `SDDP.train`. │ │ In a future release, this warning may turn into an error. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/algorithm.jl:1181 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 4.00000e+00 existing cuts : true options solver : Asynchronous mode with 4 workers. risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [1e+00, 6e+00] rhs range [4e+00, 4e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 5.000000e+00 6.000000e+00 6.915872e-01 48 1 20 9.000000e+00 6.000000e+00 1.039173e+00 162 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.039173e+00 total solves : 162 best bound : 6.000000e+00 simulation ci : 5.900000e+00 ± 9.633534e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: risk_measures.jl ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 ┌ Warning: Radius is very small. You should probably use `SDDP.Expectation()` instead. └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/risk_measures.jl:528 [ Info: sampling_schemes.jl [ Info: stopping_rules.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [0e+00, 0e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 4.001951e-01 4 1 50 0.000000e+00 0.000000e+00 6.857090e-01 200 1 ------------------------------------------------------------------- status : first_stage_stopping total time (s) : 6.857090e-01 total solves : 200 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 Simulated policy value: [ 5.035598e+00, 6.964402e+00] Simulated policy value: [ 5.282880e+00, 7.117120e+00] Simulated policy value: [ 5.606329e+00, 7.393671e+00] ┌ Warning: Are you really sure you want to use this stopping rule? Read why we don't recommend it by typing `? SDDP.Statistical` into the REPL to read the docstring. │ │ If you understand what you are doing, you can disable this warning with `SDDP.Statistical(; disable_warning = true)` └ @ SDDP ~/.julia/packages/SDDP/ScjyB/src/plugins/stopping_rules.jl:132 [ Info: threaded.jl [ Info: value_functions.jl [ Info: visualization.jl Precompiling packages... 9882.7 ms ✓ PlotThemes 9115.6 ms ✓ RecipesPipeline 8211.3 ms ✓ libdecor_jll 1757.5 ms ✓ Qt6Base_jll 2745.2 ms ✓ FFMPEG 2529.8 ms ✓ GLFW_jll 1763.2 ms ✓ Qt6ShaderTools_jll 5918.6 ms ✓ GR_jll 1767.5 ms ✓ Qt6Declarative_jll 1871.8 ms ✓ Qt6Wayland_jll 7287.5 ms ✓ GR 157704.8 ms ✓ Plots 12 dependencies successfully precompiled in 212 seconds. 165 already precompiled. ┌ Warning: `SDDP.save` is deprecated. Use `SDDP.plot` instead. │ caller = test_SpaghettiPlot() at visualization.jl:51 └ @ Core ~/.julia/packages/SDDP/ScjyB/test/visualization/visualization.jl:51 [ 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 6.585547e+00 5 1 20 0.000000e+00 -1.000000e+01 7.258719e+00 104 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.258719e+00 total solves : 104 best bound : -1.000000e+01 simulation ci : -1.100000e+01 ± 4.474009e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: FAST_production_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -5.320000e+00 -2.396000e+01 8.230000e-01 52 1 10 -2.396000e+01 -2.396000e+01 8.322558e-01 92 1 15 -4.260000e+01 -2.396000e+01 8.432438e-01 132 1 20 -2.396000e+01 -2.396000e+01 8.555038e-01 172 1 25 -5.320000e+00 -2.396000e+01 8.704200e-01 224 1 30 -5.320000e+00 -2.396000e+01 8.845758e-01 264 1 35 -2.396000e+01 -2.396000e+01 8.992260e-01 304 1 40 -2.396000e+01 -2.396000e+01 9.163818e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.163818e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -1.868714e+01 ± 3.990349e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 1.30s / 67.1% 11.7MiB / 52.3% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── forward_pass 40 548ms 62.9% 13.7ms 659KiB 10.5% 16.5KiB solve_subproblem 120 545ms 62.6% 4.54ms 486KiB 7.8% 4.05KiB get_dual_solution 120 75.8μs 0.0% 632ns 13.1KiB 0.2% 112B sample_scenario 40 532μs 0.1% 13.3μs 22.3KiB 0.4% 572B backward_pass 40 311ms 35.7% 7.78ms 5.28MiB 86.4% 135KiB solve_subproblem 160 31.3ms 3.6% 196μs 746KiB 11.9% 4.66KiB get_dual_solution 160 1.69ms 0.2% 10.5μs 195KiB 3.1% 1.22KiB prepare_backward_pass 160 150μs 0.0% 937ns 15.0KiB 0.2% 96.0B calculate_bound 40 11.6ms 1.3% 290μs 185KiB 3.0% 4.63KiB get_dual_solution 40 20.9μs 0.0% 522ns 4.38KiB 0.1% 112B get_dual_solution 36 21.3μs 0.0% 593ns 3.94KiB 0.1% 112B ──────────────────────────────────────────────────────────────────────────────────── ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-01, 3e+00] bounds range [5e+01, 5e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 -2.396000e+01 -2.396000e+01 4.579830e-01 52 1 10 -2.396000e+01 -2.396000e+01 4.695311e-01 92 1 15 -2.396000e+01 -2.396000e+01 4.833031e-01 132 1 20 -4.260000e+01 -2.396000e+01 4.976621e-01 172 1 25 -5.320000e+00 -2.396000e+01 5.165169e-01 224 1 30 -2.396000e+01 -2.396000e+01 5.361860e-01 264 1 35 -2.396000e+01 -2.396000e+01 5.580730e-01 304 1 40 -5.320000e+00 -2.396000e+01 5.818281e-01 344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.818281e-01 total solves : 344 best bound : -2.396000e+01 simulation ci : -2.237170e+01 ± 4.300524e+00 numeric issues : 0 ------------------------------------------------------------------- ──────────────────────────────────────────────────────────────────────────────────── Time Allocations ─────────────────────── ──────────────────────── Tot / % measured: 594ms / 94.5% 12.3MiB / 93.8% Section ncalls time %tot avg alloc %tot avg ──────────────────────────────────────────────────────────────────────────────────── backward_pass 40 289ms 51.4% 7.22ms 10.7MiB 92.8% 274KiB solve_subproblem 160 32.5ms 5.8% 203μs 747KiB 6.3% 4.67KiB get_dual_solution 160 1.91ms 0.3% 12.0μs 195KiB 1.6% 1.22KiB prepare_backward_pass 160 180μs 0.0% 1.12μs 15.0KiB 0.1% 96.0B forward_pass 40 259ms 46.2% 6.48ms 659KiB 5.6% 16.5KiB solve_subproblem 120 256ms 45.6% 2.14ms 486KiB 4.1% 4.05KiB get_dual_solution 120 67.4μs 0.0% 562ns 13.1KiB 0.1% 112B sample_scenario 40 595μs 0.1% 14.9μs 22.5KiB 0.2% 575B calculate_bound 40 13.3ms 2.4% 332μs 187KiB 1.6% 4.67KiB get_dual_solution 40 25.7μs 0.0% 643ns 4.38KiB 0.0% 112B get_dual_solution 36 18.7μs 0.0% 520ns 3.94KiB 0.0% 112B ──────────────────────────────────────────────────────────────────────────────────── [ Info: FAST_quickstart.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 1 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 4] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [2, 2] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 5e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 -2.500000e+00 4.602330e-01 5 1 2 -2.500000e+00 -2.000000e+00 4.628341e-01 14 1 3 -1.000000e+00 -2.000000e+00 4.761109e-01 19 1 4 -1.000000e+00 -2.000000e+00 4.784360e-01 24 1 5 -1.000000e+00 -2.000000e+00 4.802690e-01 29 1 6 -3.000000e+00 -2.000000e+00 4.821191e-01 34 1 7 -1.000000e+00 -2.000000e+00 4.831271e-01 39 1 8 -1.000000e+00 -2.000000e+00 4.841499e-01 44 1 9 -3.000000e+00 -2.000000e+00 4.858639e-01 49 1 10 -1.000000e+00 -2.000000e+00 4.875531e-01 54 1 11 -3.000000e+00 -2.000000e+00 4.889951e-01 59 1 12 -3.000000e+00 -2.000000e+00 4.907081e-01 64 1 13 -1.000000e+00 -2.000000e+00 4.919319e-01 69 1 14 -1.000000e+00 -2.000000e+00 4.929590e-01 74 1 15 -3.000000e+00 -2.000000e+00 4.946721e-01 79 1 16 -1.000000e+00 -2.000000e+00 4.964881e-01 84 1 17 -3.000000e+00 -2.000000e+00 4.983001e-01 89 1 18 -3.000000e+00 -2.000000e+00 4.994280e-01 94 1 19 -1.000000e+00 -2.000000e+00 5.004740e-01 99 1 20 -3.000000e+00 -2.000000e+00 5.015090e-01 104 1 21 -1.000000e+00 -2.000000e+00 5.043731e-01 113 1 22 -1.000000e+00 -2.000000e+00 5.062420e-01 118 1 23 -3.000000e+00 -2.000000e+00 5.081511e-01 123 1 24 -3.000000e+00 -2.000000e+00 5.101500e-01 128 1 25 -1.000000e+00 -2.000000e+00 5.122271e-01 133 1 26 -3.000000e+00 -2.000000e+00 5.138381e-01 138 1 27 -3.000000e+00 -2.000000e+00 5.149939e-01 143 1 28 -1.000000e+00 -2.000000e+00 5.162649e-01 148 1 29 -3.000000e+00 -2.000000e+00 5.182450e-01 153 1 30 -3.000000e+00 -2.000000e+00 5.202889e-01 158 1 31 -1.000000e+00 -2.000000e+00 5.223660e-01 163 1 32 -1.000000e+00 -2.000000e+00 5.244391e-01 168 1 33 -1.000000e+00 -2.000000e+00 5.265951e-01 173 1 34 -3.000000e+00 -2.000000e+00 5.280709e-01 178 1 35 -1.000000e+00 -2.000000e+00 5.294001e-01 183 1 36 -3.000000e+00 -2.000000e+00 5.315421e-01 188 1 37 -1.000000e+00 -2.000000e+00 5.336730e-01 193 1 38 -1.000000e+00 -2.000000e+00 5.358920e-01 198 1 39 -1.000000e+00 -2.000000e+00 5.376410e-01 203 1 40 -1.000000e+00 -2.000000e+00 5.398510e-01 208 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.398510e-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 7.924578e-01 51 1 20 7.585494e+01 2.232958e+02 1.811123e+00 3612 1 30 2.138334e+03 2.336430e+02 3.505634e+00 7674 1 38 8.025312e+02 2.352957e+02 4.817287e+00 10194 1 45 4.103715e+01 2.358381e+02 5.838750e+00 11835 1 54 1.830901e+02 2.360657e+02 6.922593e+00 13446 1 63 1.493193e+03 2.362190e+02 8.832696e+00 15909 1 71 1.519535e+02 2.362929e+02 9.948084e+00 17205 1 96 9.550598e+01 2.364021e+02 1.495610e+01 22248 1 100 4.969839e+02 2.364135e+02 1.682243e+01 23928 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.682243e+01 total solves : 23928 best bound : 2.364135e+02 simulation ci : 2.345669e+02 ± 6.032770e+01 numeric issues : 0 ------------------------------------------------------------------- On average, 2.1 units of thermal are used in the first stage. [ Info: StochDynamicProgramming.jl_multistock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 3 scenarios : 1.43489e+07 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [13, 13] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 5e+00] rhs range [2e+00, 2e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.977586e+00 -4.446713e+00 1.612912e+00 1400 1 20 -4.764789e+00 -4.394789e+00 1.923323e+00 2800 1 30 -4.672487e+00 -4.377000e+00 2.251244e+00 4200 1 40 -4.483495e+00 -4.370632e+00 2.577886e+00 5600 1 50 -4.167321e+00 -4.364999e+00 2.917687e+00 7000 1 60 -4.362455e+00 -4.358864e+00 3.262706e+00 8400 1 70 -4.849916e+00 -4.355337e+00 3.613313e+00 9800 1 80 -4.861568e+00 -4.353006e+00 3.976627e+00 11200 1 90 -4.268264e+00 -4.350407e+00 4.340172e+00 12600 1 100 -4.539897e+00 -4.348641e+00 4.708920e+00 14000 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 4.708920e+00 total solves : 14000 best bound : -4.348641e+00 simulation ci : -4.325070e+00 ± 8.068871e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StochDynamicProgramming.jl_stock.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 1 scenarios : 1.00000e+05 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [3e-01, 2e+00] bounds range [5e-01, 2e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -1.671715e+00 -1.476962e+00 8.447568e-01 1050 1 20 -1.529197e+00 -1.471817e+00 9.284940e-01 1600 1 30 -1.410768e+00 -1.471408e+00 1.121852e+00 2650 1 40 -1.596461e+00 -1.471258e+00 1.215270e+00 3200 1 50 -1.002277e+00 -1.471216e+00 1.416873e+00 4250 1 60 -1.085156e+00 -1.471164e+00 1.516979e+00 4800 1 70 -1.391746e+00 -1.471164e+00 1.749801e+00 5850 1 80 -1.448703e+00 -1.471132e+00 1.855381e+00 6400 1 90 -1.488989e+00 -1.471087e+00 2.072767e+00 7450 1 100 -1.564260e+00 -1.471075e+00 2.189630e+00 8000 1 110 -1.738157e+00 -1.471075e+00 2.302720e+00 8550 1 120 -1.591292e+00 -1.471075e+00 2.420036e+00 9100 1 130 -1.271481e+00 -1.471075e+00 2.536044e+00 9650 1 140 -1.249746e+00 -1.471075e+00 2.661028e+00 10200 1 150 -1.536222e+00 -1.471075e+00 2.785027e+00 10750 1 160 -1.565422e+00 -1.471075e+00 2.922737e+00 11300 1 170 -1.631076e+00 -1.471075e+00 3.051197e+00 11850 1 180 -1.494909e+00 -1.471075e+00 3.187647e+00 12400 1 182 -9.083563e-01 -1.471075e+00 3.212470e+00 12510 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.212470e+00 total solves : 12510 best bound : -1.471075e+00 simulation ci : -1.462065e+00 ± 2.699238e-02 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_2stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 4 scenarios : 2.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+06] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.455904e+05 3.147347e+05 2.965190e-01 54 1 20 3.336455e+05 3.402383e+05 3.100779e-01 104 1 30 3.993519e+05 3.403155e+05 3.228719e-01 158 1 40 3.337559e+05 3.403155e+05 3.340819e-01 208 1 48 3.337559e+05 3.403155e+05 3.448689e-01 248 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.448689e-01 total solves : 248 best bound : 3.403155e+05 simulation ci : 1.298444e+08 ± 1.785864e+08 numeric issues : 0 ------------------------------------------------------------------- [ Info: StructDualDynProg.jl_prob5.2_3stages.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [29, 29] AffExpr in MOI.EqualTo{Float64} : [4, 5] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.EqualTo{Float64} : [3, 3] VariableRef in MOI.GreaterThan{Float64} : [22, 22] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+05] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.403329e+05 3.509666e+05 4.751689e-01 92 1 20 4.506600e+05 4.054833e+05 4.973199e-01 172 1 30 3.959476e+05 4.067125e+05 5.190229e-01 264 1 40 4.497721e+05 4.067125e+05 5.383921e-01 344 1 47 3.959476e+05 4.067125e+05 5.551250e-01 400 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.551250e-01 total solves : 400 best bound : 4.067125e+05 simulation ci : 2.696242e+07 ± 3.645299e+07 numeric issues : 0 ------------------------------------------------------------------- [ Info: agriculture_mccardle_farm.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 10 state variables : 4 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [24, 24] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [1, 1] AffExpr in MOI.LessThan{Float64} : [1, 6] VariableRef in MOI.GreaterThan{Float64} : [20, 20] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 8e+01] objective range [1e+00, 1e+03] bounds range [6e+01, 6e+01] rhs range [2e+02, 3e+03] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 8.316000e+03 0.000000e+00 7.223598e+00 14 1 40 2.308500e+03 4.074139e+03 8.033725e+00 776 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.033725e+00 total solves : 776 best bound : 4.074139e+03 simulation ci : 4.224313e+03 ± 6.692189e+02 numeric issues : 0 ------------------------------------------------------------------- [ Info: air_conditioning.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 7.000000e+04 6.250000e+04 2.517147e+00 8 1 5L 4.000000e+04 6.250000e+04 3.641778e+00 52 1 11L 4.000000e+04 6.250000e+04 4.741269e+00 100 1 17L 4.000000e+04 6.250000e+04 5.876319e+00 148 1 20L 6.000000e+04 6.250000e+04 6.544326e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 6.544326e+00 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.475000e+04 ± 7.336233e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.Integer : [3, 3] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 5.986180e-01 8 1 15 5.500000e+04 6.250000e+04 1.658773e+00 132 1 20 4.000000e+04 6.250000e+04 2.033237e+00 172 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.033237e+00 total solves : 172 best bound : 6.250000e+04 simulation ci : 5.950000e+04 ± 8.933885e+03 numeric issues : 0 ------------------------------------------------------------------- Lower bound is: 62500.0 With first stage solutions 200.0 (production) and 100.0 (stored_production). [ Info: air_conditioning_forward.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 5] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [2, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 3e+02] bounds range [1e+02, 2e+02] rhs range [1e+02, 3e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.000000e+04 6.250000e+04 8.414881e-01 5 1 10 4.000000e+04 6.250000e+04 1.573025e+00 50 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.573025e+00 total solves : 50 best bound : 6.250000e+04 simulation ci : 5.450000e+04 ± 1.135842e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 1.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 9.000000e+00 7.145710e-01 6 1 20L 9.000000e+00 9.000000e+00 8.496602e-01 123 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.496602e-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 2.364148e+00 87 1 10 -1.109375e+01 2.605769e-01 2.378057e+00 142 1 15 3.105797e+00 5.434132e-01 2.393865e+00 197 1 20 -2.463349e+01 1.503415e+00 2.408026e+00 252 1 25 -1.421085e-14 1.514085e+00 2.421379e+00 307 1 30 4.864000e+01 1.514085e+00 5.163733e+00 394 1 35 4.864000e+01 1.514085e+00 5.182208e+00 449 1 40 -8.870299e+00 1.514085e+00 5.200261e+00 504 1 45 -1.428571e+00 1.514085e+00 5.218800e+00 559 1 48 -1.428571e+00 1.514085e+00 5.232170e+00 592 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.232170e+00 total solves : 592 best bound : 1.514085e+00 simulation ci : 2.494033e+00 ± 5.472486e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: asset_management_stagewise.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.395796e+01 1.428818e+00 2.327430e+00 278 1 20 1.440356e+01 1.278425e+00 2.370626e+00 428 1 30 8.388546e+00 1.278425e+00 2.449149e+00 706 1 40 6.666667e-03 1.278410e+00 2.495569e+00 856 1 50 -5.614035e+00 1.278410e+00 2.572497e+00 1134 1 60 1.426676e+01 1.278410e+00 2.622627e+00 1284 1 64 1.261296e+01 1.278410e+00 2.644811e+00 1344 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 2.644811e+00 total solves : 1344 best bound : 1.278410e+00 simulation ci : 8.172580e-01 ± 5.385320e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 7 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : #108 sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [5, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [2, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [2e-02, 4e+00] bounds range [1e+03, 1e+03] rhs range [6e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 1.111809e+00 1.278488e+00 1.176055e+00 278 1 20 1.111084e+01 1.278410e+00 1.232399e+00 428 1 30 2.293779e+01 1.278410e+00 1.326564e+00 706 1 40 1.426676e+01 1.278410e+00 1.425509e+00 856 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.425509e+00 total solves : 856 best bound : 1.278410e+00 simulation ci : 3.654300e+00 ± 6.176856e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: belief.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 4 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 2e+00] bounds range [2e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 4.787277e+00 9.346930e+00 6.871001e+00 900 1 20 6.374753e+00 1.361934e+01 7.265836e+00 1720 1 30 2.848217e+01 1.624016e+01 8.161798e+00 3036 1 40 1.973944e+01 1.776547e+01 9.249376e+00 4192 1 50 4.000000e+00 1.889360e+01 1.010886e+01 5020 1 60 1.142478e+01 1.907862e+01 1.114276e+01 5808 1 70 9.386421e+00 1.961295e+01 1.216000e+01 6540 1 80 5.667851e+01 1.890911e+01 1.296937e+01 7088 1 90 3.740597e+01 1.993139e+01 1.478305e+01 8180 1 100 9.867183e+00 2.001688e+01 1.558892e+01 8664 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.558892e+01 total solves : 8664 best bound : 2.001688e+01 simulation ci : 2.301336e+01 ± 4.670816e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: biobjective_hydro.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 5] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 0.000000e+00 0.000000e+00 3.667102e+00 36 1 10 0.000000e+00 0.000000e+00 3.727230e+00 360 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 3.727230e+00 total solves : 360 best bound : 0.000000e+00 simulation ci : 0.000000e+00 ± 0.000000e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 7] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.500000e+02 5.500000e+02 8.472919e-03 407 1 10 2.850000e+02 5.728212e+02 8.443213e-02 731 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.443213e-02 total solves : 731 best bound : 5.728212e+02 simulation ci : 6.480000e+02 ± 1.400040e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 13] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.150000e+02 3.347014e+02 8.942842e-03 778 1 10 2.825000e+02 3.465177e+02 8.684802e-02 1102 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.684802e-02 total solves : 1102 best bound : 3.465177e+02 simulation ci : 3.598954e+02 ± 6.281469e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 20] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.387500e+02 1.994007e+02 8.615017e-03 1149 1 10 2.587500e+02 2.052799e+02 8.296704e-02 1473 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.296704e-02 total solves : 1473 best bound : 2.052799e+02 simulation ci : 2.206923e+02 ± 2.764045e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 24] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 9.375000e+02 4.637735e+02 9.274960e-03 1520 1 10 2.875000e+02 4.661908e+02 9.510708e-02 1844 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.510708e-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 1.147985e-02 1891 1 10 1.000000e+02 1.129771e+02 8.782697e-02 2215 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.782697e-02 total solves : 2215 best bound : 1.129771e+02 simulation ci : 1.068750e+02 ± 2.168477e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 34] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.562500e+02 2.788383e+02 9.557009e-03 2262 1 10 1.625000e+02 2.794553e+02 9.307694e-02 2586 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.307694e-02 total solves : 2586 best bound : 2.794553e+02 simulation ci : 2.690625e+02 ± 6.720434e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 37] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 4.810804e+02 4.073537e+02 9.948969e-03 2633 1 10 5.487500e+02 4.077574e+02 9.559178e-02 2957 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.559178e-02 total solves : 2957 best bound : 4.077574e+02 simulation ci : 3.863418e+02 ± 9.936379e+01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 43] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 2.718750e+02 5.198033e+02 1.063704e-02 3004 1 10 6.771875e+02 5.210100e+02 9.655499e-02 3328 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 9.655499e-02 total solves : 3328 best bound : 5.210100e+02 simulation ci : 5.831217e+02 ± 1.295425e+02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 1.33100e+03 existing cuts : true options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 4] AffExpr in MOI.GreaterThan{Float64} : [3, 50] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.LessThan{Float64} : [5, 6] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 7.812500e+01 5.720558e+01 9.309053e-03 3375 1 10 5.312500e+01 5.938345e+01 8.483601e-02 3699 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 8.483601e-02 total solves : 3699 best bound : 5.938345e+01 simulation ci : 6.187500e+01 ± 1.306667e+01 numeric issues : 0 ------------------------------------------------------------------- [ Info: booking_management.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 2 scenarios : 3.20000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [10, 10] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.GreaterThan{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.GreaterThan{Float64} : [5, 6] VariableRef in MOI.LessThan{Float64} : [6, 6] VariableRef in MOI.ZeroOne : [5, 5] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 5 8.000000e+00 9.440450e+00 2.353074e+00 235 1 10 1.000000e+01 9.159200e+00 2.853524e+00 310 1 15 1.000000e+01 9.159200e+00 3.407106e+00 385 1 20 1.000000e+01 9.159200e+00 3.937117e+00 460 1 25 1.000000e+01 9.159200e+00 6.834037e+00 695 1 30 4.000000e+00 9.159200e+00 7.342071e+00 770 1 35 1.000000e+01 9.159200e+00 7.851111e+00 845 1 40 1.000000e+01 9.159200e+00 8.406139e+00 920 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 8.406139e+00 total solves : 920 best bound : 9.159200e+00 simulation ci : 7.200000e+00 ± 8.485598e-01 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 4 scenarios : 2.16000e+02 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [18, 18] AffExpr in MOI.EqualTo{Float64} : [4, 4] AffExpr in MOI.GreaterThan{Float64} : [4, 4] AffExpr in MOI.LessThan{Float64} : [12, 12] VariableRef in MOI.GreaterThan{Float64} : [9, 10] VariableRef in MOI.LessThan{Float64} : [10, 10] VariableRef in MOI.ZeroOne : [9, 9] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 4e+00] bounds range [1e+00, 2e+01] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.000000e+00 6.959189e+00 2.320061e+00 510 1 20 1.000000e+01 6.834387e+00 4.046464e+00 720 1 30 7.000000e+00 6.834387e+00 8.095465e+00 1230 1 40 1.000000e+01 6.823805e+00 9.831098e+00 1440 1 50 3.000000e+00 6.823805e+00 1.409098e+01 1950 1 60 2.000000e+00 6.823805e+00 1.582944e+01 2160 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.582944e+01 total solves : 2160 best bound : 6.823805e+00 simulation ci : 6.183333e+00 ± 6.694539e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: generation_expansion.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 5.299676e+06 2.074407e+06 1.171096e+01 920 1 20 6.049875e+06 2.075240e+06 1.434795e+01 1340 1 30 5.496647e+05 2.078257e+06 2.449703e+01 2260 1 40 3.985383e+04 2.078257e+06 2.698786e+01 2680 1 50 2.994548e+05 2.078257e+06 3.715179e+01 3600 1 60 3.799457e+06 2.078257e+06 3.977975e+01 4020 1 61 3.549665e+06 2.078257e+06 4.004181e+01 4062 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 4.004181e+01 total solves : 4062 best bound : 2.078257e+06 simulation ci : 2.437601e+06 ± 5.082681e+05 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 5 state variables : 5 scenarios : 3.27680e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [14, 14] AffExpr in MOI.GreaterThan{Float64} : [7, 7] AffExpr in MOI.LessThan{Float64} : [4, 4] VariableRef in MOI.GreaterThan{Float64} : [8, 8] VariableRef in MOI.Integer : [5, 5] VariableRef in MOI.LessThan{Float64} : [5, 6] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+05] bounds range [1e+00, 1e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10L 2.049870e+06 2.079457e+06 3.024179e+01 920 1 20L 2.799668e+06 2.079457e+06 4.978488e+01 1340 1 30L 3.799443e+06 2.079457e+06 7.801368e+01 2260 1 40L 4.299882e+06 2.079457e+06 9.794903e+01 2680 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 9.794903e+01 total solves : 2680 best bound : 2.079457e+06 simulation ci : 1.602238e+06 ± 4.944385e+05 numeric issues : 0 ------------------------------------------------------------------- [ Info: hydro_valley.jl [ Info: infinite_horizon_hydro_thermal.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.188534e+02 2.863010e+00 1914 1 200 0.000000e+00 1.191645e+02 3.316322e+00 3840 1 300 7.500000e+01 1.191666e+02 3.819231e+00 5738 1 328 2.500000e+00 1.191667e+02 3.917846e+00 6034 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.917846e+00 total solves : 6034 best bound : 1.191667e+02 simulation ci : 2.272866e+01 ± 3.596240e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 128.14 ± 13.91 ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [8, 8] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 5] VariableRef in MOI.LessThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+01] bounds range [5e+00, 2e+01] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 100 1.000000e+01 1.191232e+02 9.018261e-01 2806 1 200 0.000000e+00 1.191666e+02 1.470453e+00 4749 1 287 5.000000e+00 1.191667e+02 1.988993e+00 5662 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.988993e+00 total solves : 5662 best bound : 1.191667e+02 simulation ci : 2.112369e+01 ± 3.684376e+00 numeric issues : 0 ------------------------------------------------------------------- Confidence_interval = 122.02 ± 14.06 [ Info: infinite_horizon_trivial.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 2.000000e+01 1.998872e+01 4.308310e-01 1033 1 20 8.000000e+00 2.000000e+01 4.624999e-01 1209 1 30 1.200000e+01 2.000000e+01 6.116259e-01 2304 1 40 3.000000e+01 2.000000e+01 7.159760e-01 2594 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 7.159760e-01 total solves : 2594 best bound : 2.000000e+01 simulation ci : 1.970000e+01 ± 4.721453e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: inner_hydro_1d.jl Building and solving primal outer model for lower bounds ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 4 state variables : 1 scenarios : 1.00000e+03 existing cuts : false options solver : serial mode risk measure : A convex combination of 0.5 * SDDP.Expectation() + 0.5 * SDDP.AVaR(0.2) sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 2] VariableRef in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [7, 7] VariableRef in MOI.LessThan{Float64} : [6, 7] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 5e+01] bounds range [2e+01, 2e+02] rhs range [8e+01, 8e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.948878e+03 2.847167e+03 6.610830e-01 35 1 10 7.500000e+02 2.935390e+03 7.243102e-01 350 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 7.243102e-01 total solves : 350 best bound : 2.935390e+03 simulation ci : 1.544902e+03 ± 5.533339e+02 numeric issues : 0 ------------------------------------------------------------------- Building and solving inner model for upper bounds: Node: 3 - elapsed time: 0.36 plus 0.59 for vertex selection. Node: 2 - elapsed time: 0.3 plus 0.28 for vertex selection. Node: 1 - elapsed time: 0.32 plus 0.11 for vertex selection. First-stage upper bound: 2969.680973503913 Total time for upper bound: 1.962381579 Bounds: Risk-neutral confidence interval: 1411.99 ± 82.02 Risk-adjusted lower bound: 2935.39 Risk-adjusted upper bound: 2969.68 [ Info: no_strong_duality.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 1 state variables : 1 scenarios : Inf existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [3, 3] AffExpr in MOI.EqualTo{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [1, 1] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 1e+00] bounds range [0e+00, 0e+00] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 1.000000e+00 1.500000e+00 2.721140e-01 3 1 40 2.000000e+00 2.000000e+00 3.807731e-01 604 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.807731e-01 total solves : 604 best bound : 2.000000e+00 simulation ci : 2.150000e+00 ± 5.038753e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: objective_state_newsvendor.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.675000e+00 4.115510e+00 1.270612e+00 1350 1 20 5.062500e+00 4.110713e+00 1.498337e+00 2700 1 30 4.500000e+00 4.104200e+00 1.750287e+00 4050 1 40 3.812500e+00 4.102669e+00 1.997303e+00 5400 1 50 4.725000e+00 4.095504e+00 2.276446e+00 6750 1 60 4.050000e+00 4.092999e+00 2.542363e+00 8100 1 70 4.606250e+00 4.091524e+00 2.811825e+00 9450 1 80 3.875000e+00 4.089694e+00 3.086979e+00 10800 1 90 3.750000e+00 4.089490e+00 3.363718e+00 12150 1 100 5.125000e+00 4.087894e+00 3.661480e+00 13500 1 110 4.500000e+00 4.087478e+00 3.948016e+00 14850 1 120 3.650000e+00 4.086704e+00 4.233254e+00 16200 1 130 4.406250e+00 4.086063e+00 4.522874e+00 17550 1 140 3.375000e+00 4.085981e+00 4.810626e+00 18900 1 150 3.000000e+00 4.085945e+00 5.118463e+00 20250 1 160 3.812500e+00 4.085838e+00 5.423957e+00 21600 1 170 4.250000e+00 4.085728e+00 5.741313e+00 22950 1 180 3.243750e+00 4.085593e+00 6.046831e+00 24300 1 190 4.306250e+00 4.085487e+00 6.359280e+00 25650 1 200 5.237500e+00 4.085446e+00 6.691741e+00 27000 1 210 4.500000e+00 4.085441e+00 7.024661e+00 28350 1 220 3.612500e+00 4.085405e+00 7.350470e+00 29700 1 230 3.700000e+00 4.085382e+00 7.688400e+00 31050 1 240 3.437500e+00 4.085254e+00 7.988612e+00 32400 1 250 4.100000e+00 4.085115e+00 8.293084e+00 33750 1 260 3.000000e+00 4.084973e+00 8.616872e+00 35100 1 270 4.918750e+00 4.084943e+00 8.955564e+00 36450 1 280 2.756250e+00 4.084920e+00 9.306095e+00 37800 1 290 3.737500e+00 4.084868e+00 9.649648e+00 39150 1 300 5.750000e+00 4.084868e+00 1.001534e+01 40500 1 310 5.156250e+00 4.084858e+00 1.038103e+01 41850 1 320 3.131250e+00 4.084855e+00 1.073595e+01 43200 1 330 4.125000e+00 4.084846e+00 1.120578e+01 44550 1 340 5.875000e+00 4.084820e+00 1.155178e+01 45900 1 350 4.587500e+00 4.084810e+00 1.201324e+01 47250 1 360 5.087500e+00 4.084805e+00 1.237898e+01 48600 1 370 4.393750e+00 4.084802e+00 1.274658e+01 49950 1 380 4.750000e+00 4.084792e+00 1.311735e+01 51300 1 390 4.437500e+00 4.084785e+00 1.347080e+01 52650 1 400 4.181250e+00 4.084785e+00 1.377512e+01 54000 1 410 3.650000e+00 4.084777e+00 1.411423e+01 55350 1 420 3.750000e+00 4.084769e+00 1.445838e+01 56700 1 430 3.725000e+00 4.084762e+00 1.480506e+01 58050 1 440 4.218750e+00 4.084751e+00 1.518449e+01 59400 1 450 5.500000e+00 4.084751e+00 1.552489e+01 60750 1 460 3.637500e+00 4.084747e+00 1.585441e+01 62100 1 470 2.993750e+00 4.084743e+00 1.619649e+01 63450 1 480 5.237500e+00 4.084743e+00 1.655623e+01 64800 1 490 4.212500e+00 4.084743e+00 1.689045e+01 66150 1 500 3.843750e+00 4.084743e+00 1.721862e+01 67500 1 510 3.425000e+00 4.084743e+00 1.754713e+01 68850 1 520 4.293750e+00 4.084743e+00 1.786484e+01 70200 1 530 2.818750e+00 4.084740e+00 1.821768e+01 71550 1 540 4.668750e+00 4.084740e+00 1.854470e+01 72900 1 550 2.750000e+00 4.084740e+00 1.887947e+01 74250 1 560 4.100000e+00 4.084740e+00 1.923411e+01 75600 1 570 3.200000e+00 4.084738e+00 1.958897e+01 76950 1 580 3.525000e+00 4.084738e+00 1.994108e+01 78300 1 582 3.362500e+00 4.084738e+00 2.000964e+01 78570 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.000964e+01 total solves : 78570 best bound : 4.084738e+00 simulation ci : 4.066001e+00 ± 6.264482e-02 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 1 scenarios : 8.51840e+04 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [6, 6] AffExpr in MOI.EqualTo{Float64} : [1, 3] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [3, 4] VariableRef in MOI.LessThan{Float64} : [3, 3] numerical stability report matrix range [8e-01, 2e+00] objective range [1e+00, 2e+00] bounds range [1e+00, 1e+02] rhs range [5e+01, 5e+01] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 2.903414e+00 6.302990e+00 1.028201e+00 1350 1 20 5.375000e+00 6.290241e+00 1.746902e+00 2700 1 30 3.825000e+00 4.403676e+00 2.728987e+00 4050 1 40 4.725000e+00 4.337977e+00 3.808781e+00 5400 1 50 4.475000e+00 4.045697e+00 5.011377e+00 6750 1 60 4.900000e+00 4.045180e+00 6.672128e+00 8100 1 70 3.118750e+00 4.045059e+00 8.677879e+00 9450 1 80 4.437500e+00 4.043227e+00 1.091305e+01 10800 1 90 3.250000e+00 4.039717e+00 1.361332e+01 12150 1 100 4.793750e+00 4.039368e+00 1.653688e+01 13500 1 110 5.006250e+00 4.039200e+00 1.980135e+01 14850 1 111 4.256250e+00 4.039200e+00 2.012779e+01 14985 1 ------------------------------------------------------------------- status : time_limit total time (s) : 2.012779e+01 total solves : 14985 best bound : 4.039200e+00 simulation ci : 3.991290e+00 ± 1.392983e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_one.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 8 state variables : 1 scenarios : 1.00000e+08 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 7] AffExpr in MOI.EqualTo{Float64} : [1, 1] AffExpr in MOI.GreaterThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [4, 4] VariableRef in MOI.LessThan{Float64} : [1, 2] VariableRef in MOI.ZeroOne : [1, 1] numerical stability report matrix range [1e+00, 2e+00] objective range [5e-01, 1e+00] bounds range [1e+00, 1e+00] rhs range [1e+00, 1e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 3.219176e+00 1.165102e+00 1.845474e+01 1680 1 20 2.078810e+00 1.166281e+00 1.996984e+01 2560 1 30 3.973033e+00 1.166907e+00 2.158482e+01 3440 1 40 3.706337e+00 1.167312e+00 3.630548e+01 5120 1 50 3.158565e+00 1.167416e+00 3.768243e+01 6000 1 60 3.642642e+00 1.167416e+00 5.250919e+01 7680 1 70 3.451253e+00 1.167416e+00 5.406773e+01 8560 1 71 2.984727e+00 1.167416e+00 5.420088e+01 8648 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.420088e+01 total solves : 8648 best bound : 1.167416e+00 simulation ci : 3.293853e+00 ± 1.130135e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: sldp_example_two.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 4.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -4.000000e+01 -5.809615e+01 1.004253e+00 78 1 20 -4.000000e+01 -5.809615e+01 1.735990e+00 148 1 30 -4.000000e+01 -5.809615e+01 2.576019e+00 226 1 40 -4.700000e+01 -5.809615e+01 3.337153e+00 296 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.337153e+00 total solves : 296 best bound : -5.809615e+01 simulation ci : -5.346250e+01 ± 7.152725e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 9.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -6.300000e+01 -6.196125e+01 1.060472e+00 138 1 20 -4.000000e+01 -6.196125e+01 1.814467e+00 258 1 30 -7.500000e+01 -6.196125e+01 2.820475e+00 396 1 40 -4.000000e+01 -6.196125e+01 3.535470e+00 516 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 3.535470e+00 total solves : 516 best bound : -6.196125e+01 simulation ci : -6.108750e+01 ± 7.148463e+00 numeric issues : 0 ------------------------------------------------------------------- ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 2 scenarios : 3.60000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 11] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [5, 7] VariableRef in MOI.Integer : [2, 2] VariableRef in MOI.LessThan{Float64} : [4, 7] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 6e+00] objective range [1e+00, 3e+01] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 10 -7.000000e+01 -6.546793e+01 1.680189e+00 462 1 20 -5.600000e+01 -6.546793e+01 2.399047e+00 852 1 30 -4.000000e+01 -6.546793e+01 4.517182e+00 1314 1 40 -4.000000e+01 -6.546793e+01 5.275142e+00 1704 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 5.275142e+00 total solves : 1704 best bound : -6.546793e+01 simulation ci : -5.991250e+01 ± 5.174250e+00 numeric issues : 0 ------------------------------------------------------------------- [ Info: stochastic_all_blacks.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 3 state variables : 2 scenarios : 2.70000e+01 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [9, 9] AffExpr in MOI.EqualTo{Float64} : [2, 2] AffExpr in MOI.LessThan{Float64} : [2, 2] VariableRef in MOI.GreaterThan{Float64} : [2, 3] VariableRef in MOI.LessThan{Float64} : [3, 3] VariableRef in MOI.ZeroOne : [4, 4] numerical stability report matrix range [1e+00, 1e+00] objective range [1e+00, 6e+00] bounds range [1e+00, 1e+02] rhs range [0e+00, 0e+00] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1L 6.000000e+00 1.366667e+01 1.251359e+00 11 1 7L 6.000000e+00 8.000000e+00 2.344509e+00 158 1 12L 6.000000e+00 8.000000e+00 3.433970e+00 213 1 17L 6.000000e+00 8.000000e+00 4.587920e+00 268 1 21L 1.200000e+01 8.000000e+00 6.040497e+00 393 1 27L 6.000000e+00 8.000000e+00 7.241493e+00 459 1 32L 1.200000e+01 8.000000e+00 8.291359e+00 514 1 37L 6.000000e+00 8.000000e+00 9.414584e+00 569 1 40L 6.000000e+00 8.000000e+00 1.004359e+01 602 1 ------------------------------------------------------------------- status : simulation_stopping total time (s) : 1.004359e+01 total solves : 602 best bound : 8.000000e+00 simulation ci : 8.400000e+00 ± 9.462496e-01 numeric issues : 0 ------------------------------------------------------------------- [ Info: the_farmers_problem.jl ------------------------------------------------------------------- SDDP.jl (c) Oscar Dowson and contributors, 2017-25 ------------------------------------------------------------------- problem nodes : 2 state variables : 3 scenarios : 3.00000e+00 existing cuts : false options solver : serial mode risk measure : SDDP.Expectation() sampling scheme : SDDP.InSampleMonteCarlo subproblem structure VariableRef : [7, 19] AffExpr in MOI.EqualTo{Float64} : [3, 3] AffExpr in MOI.GreaterThan{Float64} : [3, 3] AffExpr in MOI.LessThan{Float64} : [1, 1] VariableRef in MOI.GreaterThan{Float64} : [3, 16] VariableRef in MOI.LessThan{Float64} : [1, 2] numerical stability report matrix range [1e+00, 2e+01] objective range [1e+00, 1e+03] bounds range [6e+03, 5e+05] rhs range [2e+02, 5e+02] ------------------------------------------------------------------- iteration simulation bound time (s) solves pid ------------------------------------------------------------------- 1 -9.800000e+04 4.922260e+05 1.016000e+00 6 1 40 1.093500e+05 1.083900e+05 1.070389e+00 240 1 ------------------------------------------------------------------- status : iteration_limit total time (s) : 1.070389e+00 total solves : 240 best bound : 1.083900e+05 simulation ci : 9.772505e+04 ± 1.969816e+04 numeric issues : 0 ------------------------------------------------------------------- [ Info: vehicle_location.jl Test Summary: | Pass Total Time SDDP.jl | 2455 2455 42m48.9s Testing SDDP tests passed Testing completed after 2569.09s PkgEval succeeded after 2705.94s