Package evaluation to test SDPLRPlus on Julia 1.14.0-DEV.2064 (1d5dcac2d2*) started at 2026-04-21T21:03:30.170 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 15.46s ################################################################################ # Installation # Installing SDPLRPlus... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [9040bce9] + SDPLRPlus v0.2.0 Updating `~/.julia/environments/v1.14/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.8.0 [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [e2d170a0] + DataValueInterfaces v1.0.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [ffbed154] + DocStringExtensions v0.9.5 [e2ba6199] + ExprTools v0.1.10 [9aa1b823] + FastClosures v0.3.2 [1a297f60] + FillArrays v1.16.0 [f6369f11] + ForwardDiff v1.3.3 [408c25d7] + GenericArpack v0.2.1 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.1 [682c06a0] + JSON v1.5.0 [4076af6c] + JuMP v1.30.0 ⌅ [0b1a1467] + KrylovKit v0.9.5 [b964fa9f] + LaTeXStrings v1.4.0 [5c8ed15e] + LinearOperators v2.13.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [607ca3ad] + LowRankOpt v0.2.1 [d05aeea4] + LuxurySparse v0.8.1 [33e6dc65] + MKL v0.9.1 [0c723cd3] + MKLSparse v3.0.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.50.1 [d8a4904e] + MutableArithmetics v1.7.1 [a4795742] + NLPModels v0.21.12 [792afdf1] + NLPModelsJuMP v0.13.5 [77ba4419] + NaNMath v1.1.3 [bac558e1] + OrderedCollections v1.8.1 [65ce6f38] + PackageExtensionCompat v1.0.2 [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.3 [3a141323] + PolynomialRoots v1.0.0 [f27b6e38] + Polynomials v4.1.1 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.3.2 [189a3867] + Reexport v1.2.2 [9040bce9] + SDPLRPlus v0.2.0 [efcf1570] + Setfield v1.1.2 [ff4d7338] + SolverCore v0.3.10 [276daf66] + SpecialFunctions v2.7.2 [90137ffa] + StaticArrays v1.9.18 [1e83bf80] + StaticArraysCore v1.4.4 [10745b16] + Statistics v1.11.1 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.7.2 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [a759f4b9] + TimerOutputs v0.5.29 [3bb67fe8] + TranscodingStreams v0.11.3 [3a884ed6] + UnPack v1.0.2 [c4a57d5a] + UnsafeArrays v1.0.9 [409d34a3] + VectorInterface v0.5.0 [6e34b625] + Bzip2_jll v1.0.9+0 [1d5cc7b8] + IntelOpenMP_jll v2025.2.0+0 [856f044c] + MKL_jll v2025.2.0+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [1317d2d5] + oneTBB_jll v2022.0.0+1 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.14.0 [de0858da] + Printf v1.11.0 [9abbd945] + Profile v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.19.0+0 [e37daf67] + LibGit2_jll v1.9.2+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2026.3.19 [4536629a] + OpenBLAS_jll v0.3.30+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.6+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.69.0+0 [3f19e933] + p7zip_jll v17.8.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 5.85s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling project... 21.5 s ✓ SDPLRPlus 1 dependency successfully precompiled in 24 seconds. 127 already precompiled. Precompilation completed after 52.2s ################################################################################ # Testing # Testing SDPLRPlus Status `/tmp/jl_K6UKtu/Project.toml` [6a86dc24] FiniteDiff v2.30.0 [d05aeea4] LuxurySparse v0.8.1 [9040bce9] SDPLRPlus v0.2.0 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_K6UKtu/Manifest.toml` [79e6a3ab] Adapt v4.5.2 [4fba245c] ArrayInterface v7.24.0 [6e4b80f9] BenchmarkTools v1.8.0 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [187b0558] ConstructionBase v1.6.0 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [e2d170a0] DataValueInterfaces v1.0.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [ffbed154] DocStringExtensions v0.9.5 [e2ba6199] ExprTools v0.1.10 [9aa1b823] FastClosures v0.3.2 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.30.0 [f6369f11] ForwardDiff v1.3.3 [408c25d7] GenericArpack v0.2.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.1 [682c06a0] JSON v1.5.0 [4076af6c] JuMP v1.30.0 ⌅ [0b1a1467] KrylovKit v0.9.5 [b964fa9f] LaTeXStrings v1.4.0 [5c8ed15e] LinearOperators v2.13.0 [2ab3a3ac] LogExpFunctions v0.3.29 [607ca3ad] LowRankOpt v0.2.1 [d05aeea4] LuxurySparse v0.8.1 [33e6dc65] MKL v0.9.1 [0c723cd3] MKLSparse v3.0.0 [1914dd2f] MacroTools v0.5.16 [b8f27783] MathOptInterface v1.50.1 [d8a4904e] MutableArithmetics v1.7.1 [a4795742] NLPModels v0.21.12 [792afdf1] NLPModelsJuMP v0.13.5 [77ba4419] NaNMath v1.1.3 [bac558e1] OrderedCollections v1.8.1 [65ce6f38] PackageExtensionCompat v1.0.2 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [3a141323] PolynomialRoots v1.0.0 [f27b6e38] Polynomials v4.1.1 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.2 [08abe8d2] PrettyTables v3.3.2 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [9040bce9] SDPLRPlus v0.2.0 [efcf1570] Setfield v1.1.2 [ff4d7338] SolverCore v0.3.10 [276daf66] SpecialFunctions v2.7.2 [90137ffa] StaticArrays v1.9.18 [1e83bf80] StaticArraysCore v1.4.4 [10745b16] Statistics v1.11.1 [892a3eda] StringManipulation v0.4.4 [ec057cc2] StructUtils v2.7.2 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.1 [a759f4b9] TimerOutputs v0.5.29 [3bb67fe8] TranscodingStreams v0.11.3 [3a884ed6] UnPack v1.0.2 [c4a57d5a] UnsafeArrays v1.0.9 [409d34a3] VectorInterface v0.5.0 [6e34b625] Bzip2_jll v1.0.9+0 [1d5cc7b8] IntelOpenMP_jll v2025.2.0+0 [856f044c] MKL_jll v2025.2.0+0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [1317d2d5] oneTBB_jll v2022.0.0+1 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0 [4af54fe1] LazyArtifacts v1.11.0 [b27032c2] LibCURL v1.0.0 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.14.0 [de0858da] Printf v1.11.0 [9abbd945] Profile v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.0.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.19.0+0 [e37daf67] LibGit2_jll v1.9.2+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2026.3.19 [4536629a] OpenBLAS_jll v0.3.30+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.6+0 [efcefdf7] PCRE2_jll v10.47.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.2+0 [3161d3a3] Zstd_jll v1.5.7+1 [8e850b90] libblastrampoline_jll v5.15.0+0 [8e850ede] nghttp2_jll v1.69.0+0 [3f19e933] p7zip_jll v17.8.0+0 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time SymLowRankMatrix tests | 200 200 5.9s [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 1 │ 5 │ 5 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2520166098752774 max_dual_value = -1.0080675187001888 duality_gap = -0.24199677764604366 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 6 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.997986386538483 max_dual_value = -1.00001496212694 duality_gap = 0.0020326685973073785 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 0 │ 6 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.997986386538483 max_dual_value = -0.9919624055536918 duality_gap = -0.006072791620997808 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 6 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.997986386538483 max_dual_value = -0.9839098489804434 duality_gap = -0.014306735086172926 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0037625343307541 max_dual_value = -0.9839098489804434 duality_gap = -0.020177341827488208 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.000451765666438 max_dual_value = -0.9839098489804434 duality_gap = -0.016812431243711817 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998255370920802 max_dual_value = -0.9839098489804434 duality_gap = -0.016175961779556432 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 0 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998255370920803 max_dual_value = -0.9839098489804434 duality_gap = -0.016175961779556547 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0001311066440757 max_dual_value = -0.9839098489804434 duality_gap = -0.016486528395300848 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000336367418696 max_dual_value = -0.9839098489804434 duality_gap = -0.016387464540713916 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999902604587334 max_dual_value = -0.9839098489804434 duality_gap = -0.016343378913172765 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 0 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999902604587334 max_dual_value = -0.9839098489804434 duality_gap = -0.016343378913172765 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000009202098781 max_dual_value = -0.9839098489804434 duality_gap = -0.01636263031112065 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000008369547952 max_dual_value = -0.9839098489804434 duality_gap = -0.016354128369612097 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 0 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000008369547952 max_dual_value = -0.9839098489804434 duality_gap = -0.016354128369612097 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999989439952686 max_dual_value = -0.9839098489804434 duality_gap = -0.016352204453992544 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999998155200126 max_dual_value = -0.9839098489804434 duality_gap = -0.01635309023102277 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 0 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999998155200127 max_dual_value = -0.9839098489804434 duality_gap = -0.016353090231022882 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 1 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.00000025012002 max_dual_value = -0.9839098489804434 duality_gap = -0.016353531938164818 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000000006920136 max_dual_value = -0.9839098489804434 duality_gap = -0.016353284761165564 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 0 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000069201358 max_dual_value = -0.9839098489804434 duality_gap = -0.01635328476116534 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ 1 │ 19 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999908805246 max_dual_value = -0.9839098489804434 duality_gap = -0.016353268459253924 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ 1 │ 20 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999977069888 max_dual_value = -0.9839098489804434 duality_gap = -0.01635327539735316 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ -1 │ 20 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 1 │ 6 │ 6 │ -1.02E+00 │ -1.05E+00 │ 1.00E+01 │ 1.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.050386112745078 max_dual_value = -1.0077225380928643 duality_gap = -0.04233662842646688 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9996140310933335 max_dual_value = -1.0000034862031888 duality_gap = 0.00038960548545858377 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999966465999827 max_dual_value = -0.9999364194162403 duality_gap = -6.023101326530679e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-04 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000030344604047 max_dual_value = -0.9999364194162403 duality_gap = -6.661927985708943e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-05 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000001919747463 max_dual_value = -0.9999364194162403 duality_gap = -6.37766134602952e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-06 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999526086434 max_dual_value = -0.9999364194162403 duality_gap = -6.353723213735221e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-07 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.999999999584894 max_dual_value = -0.9999364194162403 duality_gap = -6.358421137498675e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ -1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-07 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= [ Info: Max Cut SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬──────────┬───────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼───────────┼──────────┼──────────┼── │ │ 1 │ 2 │ 2 │ 3.81E-03 │ -2.59E-05 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴───────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = -2.5908083222191125e-5 max_dual_value = -0.9737252058393702 duality_gap = 37582.83812065813 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 3 │ -3.85E-03 │ -1.66E-05 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.657833784167259e-5 max_dual_value = -0.9737252058393702 duality_gap = 58733.79085410718 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 4 │ -6.42E-06 │ -1.38E-06 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.3804721706007024e-6 max_dual_value = -0.3096243484678743 duality_gap = 224287.728930438 ┌─────────┬───┬───────┬─────────┬──────────┬───────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼───────────┼──────────┼──────────┼── │ │ 4 │ 0 │ 4 │ 1.72E-05 │ -1.38E-06 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴───────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = -1.3804721705756862e-6 max_dual_value = -0.0019245138756856517 duality_gap = 1393.0982778979808 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 5 │ -2.22E-05 │ -2.96E-06 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -2.9592720172521945e-6 max_dual_value = -0.0019245138756856517 duality_gap = 649.3335497602014 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 6 │ -3.55E-07 │ -3.87E-08 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -3.873076821074514e-8 max_dual_value = -0.0019245138756856517 duality_gap = 49688.53533825675 ┌─────────┬───┬───────┬─────────┬──────────┬───────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼───────────┼──────────┼──────────┼── │ │ 7 │ 0 │ 6 │ 6.46E-07 │ -3.87E-08 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴───────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = -3.873076820370969e-8 max_dual_value = -0.0019245138756856517 duality_gap = 49688.535347282865 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 1 │ 7 │ -7.59E-07 │ -4.00E-08 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -3.9986032111636205e-8 max_dual_value = -0.0019245138756856517 duality_gap = 48128.65363286459 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 8 │ -1.71E-09 │ -3.48E-10 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -3.477267761649261e-10 max_dual_value = -0.0019245138756856517 duality_gap = 5.534556611326597e6 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 1 │ 9 │ -3.82E-09 │ -3.15E-10 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -3.153654895513685e-10 max_dual_value = -0.0019245138756856517 duality_gap = 6.102486239245549e6 ┌─────────┬────┬───────┬─────────┬──────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼───────────┼──────────┼──────────── │ │ 11 │ 0 │ 9 │ 3.70E-09 │ -3.15E-10 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴──────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -3.153655669940747e-10 max_dual_value = -0.0019245138756856517 duality_gap = 6.10248474068903e6 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 1 │ 10 │ -4.33E-09 │ -3.06E-10 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -3.0635094256078924e-10 max_dual_value = -0.0019245138756856517 duality_gap = 6.282055322721352e6 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 1 │ 11 │ -1.69E-11 │ -9.15E-13 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -9.153996529412932e-13 max_dual_value = -0.0019245138756856517 duality_gap = 2.1023755783460798e9 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 12 │ -2.43E-11 │ -1.66E-12 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.6574620926035718e-12 max_dual_value = -0.0019245138756856517 duality_gap = 1.161120898400233e9 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 1 │ 13 │ -3.92E-14 │ -2.59E-14 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -2.5944037142525595e-14 max_dual_value = -0.0019245138756856517 duality_gap = 7.41794295578302e10 ┌─────────┬────┬───────┬─────────┬──────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼───────────┼──────────┼──────────── │ │ 16 │ 0 │ 13 │ 9.21E-13 │ -2.60E-14 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴──────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -2.5979218776228663e-14 max_dual_value = -0.0019245138756856517 duality_gap = 7.40789741306859e10 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 14 │ -1.13E-12 │ -7.13E-14 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -7.127089439731923e-14 max_dual_value = -0.0019245138756856517 duality_gap = 2.7002802362569607e10 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 15 │ -5.88E-16 │ -3.26E-16 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -3.2578630198514164e-16 max_dual_value = -0.0019245138756856517 duality_gap = 5.907289115467778e12 ┌─────────┬────┬───────┬─────────┬──────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼───────────┼──────────┼──────────── │ │ 19 │ 0 │ 15 │ 3.22E-14 │ -2.78E-16 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴──────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -2.7755575615628914e-16 max_dual_value = -0.0019245138756856517 duality_gap = 6.9337919787248e12 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 16 │ -3.94E-14 │ -1.45E-15 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.4524968020319452e-15 max_dual_value = -0.0019245138756856517 duality_gap = 1.3249694408909775e12 ┌─────────┬────┬───────┬─────────┬──────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼───────────┼──────────┼──────────── │ │ 21 │ 1 │ 17 │ 5.59E-17 │ -1.77E-17 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴──────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.76878666345327e-17 max_dual_value = -0.0019245138756856517 duality_gap = 1.0880418285879269e14 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 22 │ 0 │ 17 │ 7.38E-16 │ 0.00E+00 │ 2.00E+00 │ 2.38E-07 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.0 max_dual_value = -0.001295558539341869 duality_gap = Inf ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ 1 │ 18 │ -9.32E-16 │ -5.51E-17 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -5.5122052803693197e-17 max_dual_value = -0.001295558539341869 duality_gap = 2.3503452310742152e13 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 24 │ 1 │ 19 │ 1.77E-17 │ 1.92E-17 │ 2.00E+00 │ 5.96E-08 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.9185097300932484e-17 max_dual_value = -0.001295558539341869 duality_gap = 6.7529422395940516e13 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 25 │ 1 │ 20 │ -5.00E-18 │ -2.52E-19 │ 2.00E+00 │ 2.98E-08 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -2.517087058425052e-19 max_dual_value = -0.001295558539341869 duality_gap = 5.147054945936209e15 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 26 │ 1 │ 21 │ 3.12E-19 │ 2.99E-19 │ 2.00E+00 │ 1.49E-08 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 2.9909264949527853e-19 max_dual_value = -0.001295558539341869 duality_gap = 4.3316294851382525e15 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 27 │ 0 │ 21 │ 1.35E-19 │ 0.00E+00 │ 2.00E+00 │ 1.00E-08 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.0 max_dual_value = -0.001295558539341869 duality_gap = Inf ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 28 │ 0 │ 21 │ 2.57E-19 │ 0.00E+00 │ 2.00E+00 │ 1.00E-08 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.0 max_dual_value = -0.001295558539341869 duality_gap = Inf [ Info: rank doubled, newrank is 2. ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 29 │ 7 │ 28 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.24550703905581 max_dual_value = -0.9903546219291567 duality_gap = -0.257637427520286 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 30 │ 1 │ 29 │ -9.99E-01 │ -1.00E+00 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0003724800635763 max_dual_value = -0.9903546219291567 duality_gap = -0.010115425235160045 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 31 │ 0 │ 29 │ -9.99E-01 │ -1.00E+00 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000372480063576 max_dual_value = -0.9903546219291567 duality_gap = -0.010115425235159821 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 32 │ 2 │ 31 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.998211875837433 max_dual_value = -0.9903546219291567 duality_gap = -0.007933778198531345 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 33 │ 0 │ 31 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9982118758374329 max_dual_value = -0.9894356683757708 duality_gap = -0.00886991215514683 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 34 │ 1 │ 32 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.002641148935133 max_dual_value = -0.9894356683757708 duality_gap = -0.013346477170203448 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 35 │ 1 │ 33 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000058869481958 max_dual_value = -0.9894356683757708 duality_gap = -0.010683078152798741 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 36 │ 0 │ 33 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000058869481958 max_dual_value = -0.9894356683757708 duality_gap = -0.010683078152798741 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 37 │ 0 │ 33 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000058869481958 max_dual_value = -0.9894356683757708 duality_gap = -0.010683078152798741 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 38 │ 0 │ 33 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000058869481958 max_dual_value = -0.9894356683757708 duality_gap = -0.010683078152798741 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 39 │ 2 │ 35 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.999968756093811 max_dual_value = -0.9894356683757708 duality_gap = -0.010645550847515933 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 40 │ 1 │ 36 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000062506369403 max_dual_value = -0.9894356683757708 duality_gap = -0.010683445724694597 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 41 │ 1 │ 37 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000016557820766 max_dual_value = -0.9894356683757708 duality_gap = -0.010678801809975769 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 42 │ 0 │ 37 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000016557820768 max_dual_value = -0.9894356683757708 duality_gap = -0.010678801809975992 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 43 │ 1 │ 38 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999979038378679 max_dual_value = -0.9894356683757708 duality_gap = -0.010675009805777243 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 44 │ 1 │ 39 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999423653507 max_dual_value = -0.9894356683757708 duality_gap = -0.010677070098879637 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 45 │ 0 │ 39 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999423653507 max_dual_value = -0.9894356683757708 duality_gap = -0.010677070098879637 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 46 │ 2 │ 41 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000001611452882 max_dual_value = -0.9894356683757708 duality_gap = -0.01067729121475861 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 47 │ 1 │ 42 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999215772112 max_dual_value = -0.9894356683757708 duality_gap = -0.01067704908878246 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 48 │ 0 │ 42 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999215772114 max_dual_value = -0.9894356683757708 duality_gap = -0.010677049088782684 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 49 │ 1 │ 43 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000618359346 max_dual_value = -0.9894356683757708 duality_gap = -0.010677190845066265 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 50 │ 1 │ 44 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000027820057 max_dual_value = -0.9894356683757708 duality_gap = -0.010677131160611029 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 50 │ -1 │ 44 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Max Cut | 3 3 1m22.8s [ Info: Minimum Bisection SDP is formed. ========================================================================================================================= SDPLRPlus.jl: a julia implementation of SDPLR with objval gap bound ========================================================================================================================= [ Info: Finish classifying constraints. ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 1 │ 4 │ 4 │ 8.80E-01 │ 7.41E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.7407185967000903 max_dual_value = 1.0332610457505838 duality_gap = -0.39494411285712727 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 2 │ 1 │ 5 │ 9.94E-01 │ 1.02E+00 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0151274678407773 max_dual_value = 1.0332610457505838 duality_gap = -0.017863350647359943 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 3 │ 1 │ 6 │ 9.99E-01 │ 9.92E-01 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9918700404177215 max_dual_value = 1.0332610457505838 duality_gap = -0.04173027074739609 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 4 │ 1 │ 7 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0016399907037206 max_dual_value = 1.0332610457505838 duality_gap = -0.031569281718322004 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 5 │ 1 │ 8 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9990305364482163 max_dual_value = 1.0332610457505838 duality_gap = -0.03426372673658688 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 6 │ 0 │ 8 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 1.56E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9990305364482162 max_dual_value = 1.0332610457505838 duality_gap = -0.034263726736587 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 7 │ 1 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0011759324762517 max_dual_value = 1.0332610457505838 duality_gap = -0.03204742766336238 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 8 │ 1 │ 10 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9999925056197632 max_dual_value = 1.0332610457505838 duality_gap = -0.03326878945977882 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 8 │ -1 │ 10 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Minimum Bisection | 1 1 1.8s Test Summary: | Total Time Lovasz Theta | 0 0.0s Test Summary: | Total Time Cut Norm | 0 0.0s [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Cut Norm SDP is formed. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time f!, g! and linesearch! | 252 252 20.1s [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time f!, g! with inequality constraints | 108 108 0.8s [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Max Cut SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Lovasz Theta SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Minimum Bisection SDP is formed. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. [ Info: μ-Conductance (inequality) SDP is formed. [ Info: Finish classifying constraints. Test Summary: | Pass Total Time 𝒜t! operator | 216 216 5.4s Testing SDPLRPlus tests passed Testing completed after 147.75s PkgEval succeeded after 242.12s