Package evaluation to test SDPLRPlus on Julia 1.14.0-DEV.2360 (7c0e770819*) started at 2026-06-13T21:53:54.955 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 14.88s ################################################################################ # 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` [523fee87] + CodecBzip2 v0.8.5 [944b1d66] + CodecZlib v0.7.8 [bbf7d656] + CommonSubexpressions v0.3.1 [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 v1.16.0 [ffbed154] + DocStringExtensions v0.9.5 [e2ba6199] + ExprTools v0.1.10 [9aa1b823] + FastClosures v0.3.2 [1a297f60] + FillArrays v1.16.0 [f6369f11] + ForwardDiff v1.4.1 [408c25d7] + GenericArpack v0.2.1 [92d709cd] + IrrationalConstants v0.2.6 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.6.1 [4076af6c] + JuMP v1.30.1 [0b1a1467] + KrylovKit v0.10.3 [b964fa9f] + LaTeXStrings v1.4.0 [5c8ed15e] + LinearOperators v2.14.1 [2ab3a3ac] + LogExpFunctions v1.0.1 [607ca3ad] + LowRankOpt v0.2.2 [d05aeea4] + LuxurySparse v0.8.1 [33e6dc65] + MKL v0.9.1 [0c723cd3] + MKLSparse v3.0.0 [1914dd2f] + MacroTools v0.5.16 [b8f27783] + MathOptInterface v1.51.1 [d8a4904e] + MutableArithmetics v1.8.0 [a4795742] + NLPModels v0.21.12 [792afdf1] + NLPModelsJuMP v0.13.5 [77ba4419] + NaNMath v1.1.4 ⌅ [bac558e1] + OrderedCollections v1.8.2 [65ce6f38] + PackageExtensionCompat v1.0.2 ⌅ [d96e819e] + Parameters v0.12.3 [69de0a69] + Parsers v2.8.5 [3a141323] + PolynomialRoots v1.0.0 [f27b6e38] + Polynomials v4.1.1 [aea7be01] + PrecompileTools v1.3.4 [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 v2.8.0 [90137ffa] + StaticArrays v1.9.18 [1e83bf80] + StaticArraysCore v1.4.4 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.8.2 [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 v2022.3.0+0 [0dad84c5] + ArgTools v1.2.0 [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 v1.14.0 [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 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.13.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.5.2+0 [deac9b47] + LibCURL_jll v8.20.0+1 [e37daf67] + LibGit2_jll v1.9.4+0 [29816b5a] + LibSSH2_jll v1.11.101+0 [14a3606d] + MozillaCACerts_jll v2026.5.14 [4536629a] + OpenBLAS_jll v0.3.33+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.7+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 5.8s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompiling project... 13.6 s ✓ LowRankOpt 25.3 s ✓ SDPLRPlus 2 dependencies successfully precompiled in 40 seconds. 117 already precompiled. Precompilation completed after 67.72s ################################################################################ # Testing # Testing SDPLRPlus Status `/tmp/jl_Rvafza/Project.toml` [6a86dc24] FiniteDiff v2.31.0 [d05aeea4] LuxurySparse v0.8.1 [9040bce9] SDPLRPlus v0.2.0 [37e2e46d] LinearAlgebra v1.14.0 [9a3f8284] Random v1.11.0 [2f01184e] SparseArrays v1.13.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_Rvafza/Manifest.toml` [79e6a3ab] Adapt v4.6.1 [4fba245c] ArrayInterface v7.25.0 [523fee87] CodecBzip2 v0.8.5 [944b1d66] CodecZlib v0.7.8 [bbf7d656] CommonSubexpressions v0.3.1 [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 v1.16.0 [ffbed154] DocStringExtensions v0.9.5 [e2ba6199] ExprTools v0.1.10 [9aa1b823] FastClosures v0.3.2 [1a297f60] FillArrays v1.16.0 [6a86dc24] FiniteDiff v2.31.0 [f6369f11] ForwardDiff v1.4.1 [408c25d7] GenericArpack v0.2.1 [92d709cd] IrrationalConstants v0.2.6 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.8.0 [682c06a0] JSON v1.6.1 [4076af6c] JuMP v1.30.1 [0b1a1467] KrylovKit v0.10.3 [b964fa9f] LaTeXStrings v1.4.0 [5c8ed15e] LinearOperators v2.14.1 [2ab3a3ac] LogExpFunctions v1.0.1 [607ca3ad] LowRankOpt v0.2.2 [d05aeea4] LuxurySparse v0.8.1 [33e6dc65] MKL v0.9.1 [0c723cd3] MKLSparse v3.0.0 [1914dd2f] MacroTools v0.5.16 [b8f27783] MathOptInterface v1.51.1 [d8a4904e] MutableArithmetics v1.8.0 [a4795742] NLPModels v0.21.12 [792afdf1] NLPModelsJuMP v0.13.5 [77ba4419] NaNMath v1.1.4 ⌅ [bac558e1] OrderedCollections v1.8.2 [65ce6f38] PackageExtensionCompat v1.0.2 ⌅ [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.5 [3a141323] PolynomialRoots v1.0.0 [f27b6e38] Polynomials v4.1.1 [aea7be01] PrecompileTools v1.3.4 [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 v2.8.0 [90137ffa] StaticArrays v1.9.18 [1e83bf80] StaticArraysCore v1.4.4 [892a3eda] StringManipulation v0.4.4 [ec057cc2] StructUtils v2.8.2 [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 v2022.3.0+0 [0dad84c5] ArgTools v1.2.0 [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 v1.14.0 [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 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v1.13.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.13.0 [f489334b] StyledStrings v1.13.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.5.2+0 [deac9b47] LibCURL_jll v8.20.0+1 [e37daf67] LibGit2_jll v1.9.4+0 [29816b5a] LibSSH2_jll v1.11.101+0 [14a3606d] MozillaCACerts_jll v2026.5.14 [4536629a] OpenBLAS_jll v0.3.33+0 [05823500] OpenLibm_jll v0.8.7+0 [458c3c95] OpenSSL_jll v3.5.7+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 5.5s [ 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 │ 3 │ 3 │ -1.12E+00 │ -1.25E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2477151368197907 max_dual_value = -0.9909457661012573 duality_gap = -0.25911546272482494 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 4 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.002525953014646 max_dual_value = -0.9909457661012573 duality_gap = -0.011685994642218794 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999035576412327 max_dual_value = -0.9909457661012573 duality_gap = -0.009039638541692015 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 0 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999035576412326 max_dual_value = -0.9909457661012573 duality_gap = -0.009039638541691902 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998905077986083 max_dual_value = -0.9909457661012573 duality_gap = -0.009026469463150265 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 0 │ 6 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998905077986084 max_dual_value = -0.9909457661012573 duality_gap = -0.009026469463150378 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.000084184471971 max_dual_value = -0.9909457661012573 duality_gap = -0.009221915752935295 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000316740096284 max_dual_value = -0.9909457661012573 duality_gap = -0.00916892550448895 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 0 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000316740096284 max_dual_value = -0.9909457661012573 duality_gap = -0.00916892550448895 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.999969603381378 max_dual_value = -0.9909457661012573 duality_gap = -0.009106287739261207 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999904582177538 max_dual_value = -0.9909457661012573 duality_gap = -0.009127333125486397 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 0 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999904582177537 max_dual_value = -0.9909457661012573 duality_gap = -0.009127333125486284 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000111953520632 max_dual_value = -0.9909457661012573 duality_gap = -0.009148259734205839 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000012317846654 max_dual_value = -0.9909457661012573 duality_gap = -0.00913820513007044 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 0 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000012317846652 max_dual_value = -0.9909457661012573 duality_gap = -0.009138205130070217 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.999998475458968 max_dual_value = -0.9909457661012573 duality_gap = -0.009135423619929684 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999997730014193 max_dual_value = -0.9909457661012573 duality_gap = -0.009136733017977135 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000820759412 max_dual_value = -0.9909457661012573 duality_gap = -0.009137044916501188 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 0 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000820759412 max_dual_value = -0.9909457661012573 duality_gap = -0.009137044916501188 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999349805102 max_dual_value = -0.9909457661012573 duality_gap = -0.009136896477064865 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 1 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999854879186 max_dual_value = -0.9909457661012573 duality_gap = -0.009136947445957508 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ 0 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999854879186 max_dual_value = -0.9909457661012573 duality_gap = -0.009136947445957508 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ 1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000189974427 max_dual_value = -0.9909457661012573 duality_gap = -0.009136981261656916 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 24 │ 1 │ 19 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 5.96E-08 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000002842773 max_dual_value = -0.9909457661012573 duality_gap = -0.00913696237750997 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 24 │ -1 │ 19 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 5.96E-08 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 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 │ 4 │ 4 │ -1.02E+00 │ -1.05E+00 │ 1.00E+01 │ 1.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0500399497966393 max_dual_value = -1.0007997995023148 duality_gap = -0.04920079951935542 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999604628308695 max_dual_value = -1.0000099806772413 duality_gap = 4.951980424473614e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 6 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999984180286521 max_dual_value = -0.9999783430224809 duality_gap = -2.0075440944556184e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-04 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0000010188412987 max_dual_value = -0.9999783430224809 duality_gap = -2.2676309918097483e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-05 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.00000006685548 max_dual_value = -0.9999783430224809 duality_gap = -2.172430348189528e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-06 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9999999971540271 max_dual_value = -0.9999783430224809 duality_gap = -2.1654600519397074e-5 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ -1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 1.00E+01 │ 1.00E-06 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 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 │ -1.12E+00 │ -1.27E+00 │ 2.00E+00 │ 5.00E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.2669296368850558 max_dual_value = -1.0679366276517548 duality_gap = -0.18633409893512046 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 2 │ 1 │ 3 │ -1.00E+00 │ -9.84E-01 │ 2.00E+00 │ 2.50E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9836057771193447 max_dual_value = -1.0027532587082115 duality_gap = 0.019466621724145865 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 3 │ 1 │ 4 │ -1.00E+00 │ -9.98E-01 │ 2.00E+00 │ 1.25E-01 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9978607280247604 max_dual_value = -0.99420847172124 duality_gap = -0.0036735316660472285 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 4 │ 1 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.25E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0011954591169425 max_dual_value = -0.99420847172124 duality_gap = -0.007027688452107164 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 5 │ 0 │ 5 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.12E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0011954591169425 max_dual_value = -0.99420847172124 duality_gap = -0.007027688452107164 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 6 │ 1 │ 6 │ -1.00E+00 │ -9.99E-01 │ 2.00E+00 │ 1.56E-02 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9991322029556408 max_dual_value = -0.99420847172124 duality_gap = -0.0049524132759364 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 7 │ 1 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.81E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998742527937432 max_dual_value = -0.99420847172124 duality_gap = -0.0056987857513366115 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 8 │ 0 │ 7 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.91E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -0.9998742527937432 max_dual_value = -0.99420847172124 duality_gap = -0.0056987857513366115 ┌─────────┬───┬───────┬─────────┬───────────┬───────────┬──────────┬──────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼───┼───────┼─────────┼───────────┼───────────┼──────────┼──────────── │ │ 9 │ 1 │ 8 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.95E-03 ⋯ └─────────┴───┴───────┴─────────┴───────────┴───────────┴──────────┴──────────── 5 columns omitted var.obj[] = -1.0001669332790482 max_dual_value = -0.99420847172124 duality_gap = -0.005993171178165901 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 10 │ 1 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.77E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000015919174563 max_dual_value = -0.99420847172124 duality_gap = -0.005841277376432646 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 11 │ 0 │ 9 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.88E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.000015919174563 max_dual_value = -0.99420847172124 duality_gap = -0.005841277376432646 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 12 │ 1 │ 10 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.44E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999789133505879 max_dual_value = -0.99420847172124 duality_gap = -0.005804055983708967 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 13 │ 1 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.22E-04 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999970576770655 max_dual_value = -0.99420847172124 duality_gap = -0.005822306005705066 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 14 │ 0 │ 11 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 6.10E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999970576770654 max_dual_value = -0.99420847172124 duality_gap = -0.005822306005704955 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 15 │ 1 │ 12 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.05E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000040044449838 max_dual_value = -0.99420847172124 duality_gap = -0.005829293240390686 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 16 │ 1 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.53E-05 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000002643755104 max_dual_value = -0.99420847172124 duality_gap = -0.0058255313840196755 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 17 │ 0 │ 13 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 7.63E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000002643755104 max_dual_value = -0.99420847172124 duality_gap = -0.0058255313840196755 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 18 │ 1 │ 14 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 3.81E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999996490168677 max_dual_value = -0.99420847172124 duality_gap = -0.005824912440749516 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 19 │ 1 │ 15 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.91E-06 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999356959184 max_dual_value = -0.99420847172124 duality_gap = -0.005825200789781811 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 20 │ 1 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 9.54E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000234610698 max_dual_value = -0.99420847172124 duality_gap = -0.005825289066188485 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 21 │ 0 │ 16 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 4.77E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -1.0000000234610695 max_dual_value = -0.99420847172124 duality_gap = -0.0058252890661882615 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 22 │ 1 │ 17 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 2.38E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999791939801 max_dual_value = -0.99420847172124 duality_gap = -0.005825244541231276 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ 1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted var.obj[] = -0.9999999967461431 max_dual_value = -0.99420847172124 duality_gap = -0.005825262195640341 ┌─────────┬────┬───────┬─────────┬───────────┬───────────┬──────────┬─────────── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ ⋯ ├─────────┼────┼───────┼─────────┼───────────┼───────────┼──────────┼─────────── │ │ 23 │ -1 │ 18 │ -1.00E+00 │ -1.00E+00 │ 2.00E+00 │ 1.19E-07 ⋯ └─────────┴────┴───────┴─────────┴───────────┴───────────┴──────────┴─────────── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Max Cut | 3 3 1m22.3s [ 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 │ 2 │ 2 │ 8.77E-01 │ 7.53E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.753278369281832 max_dual_value = 0.05246469808336207 duality_gap = 13.357813859615373 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 2 │ 1 │ 3 │ 9.97E-01 │ 1.00E+00 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0002151642541937 max_dual_value = 0.596752504351834 duality_gap = 0.6760971373561018 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 3 │ 1 │ 4 │ 1.00E+00 │ 9.95E-01 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.995019294232896 max_dual_value = 0.596752504351834 duality_gap = 0.6673902279030092 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 4 │ 1 │ 5 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0013264236255168 max_dual_value = 0.9885986943178562 duality_gap = 0.01287451559547417 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 5 │ 0 │ 5 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0013264236255168 max_dual_value = 0.9885986943178562 duality_gap = 0.01287451559547417 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 6 │ 1 │ 6 │ 1.00E+00 │ 9.98E-01 │ 2.00E+00 │ 1.56E-02 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9978695922264043 max_dual_value = 0.9885986943178562 duality_gap = 0.009377817269873181 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 7 │ 1 │ 7 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0003709850648468 max_dual_value = 0.9885986943178562 duality_gap = 0.011908058158132211 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 8 │ 1 │ 8 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 0.9998659253427734 max_dual_value = 0.9885986943178562 duality_gap = 0.01139717368602407 ┌─────────┬───┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬─── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼───┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼─── │ │ 9 │ 1 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.95E-03 │ ⋯ └─────────┴───┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴─── 5 columns omitted var.obj[] = 1.0000221820432365 max_dual_value = 0.9885986943178562 duality_gap = 0.011555232462918228 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 10 │ 0 │ 9 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 9.77E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000221820432365 max_dual_value = 0.9885986943178562 duality_gap = 0.011555232462918228 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 11 │ 1 │ 10 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 4.88E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9999664474574599 max_dual_value = 0.9885986943178562 duality_gap = 0.011498855101611853 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 12 │ 1 │ 11 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 2.44E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000045432560507 max_dual_value = 0.9885986943178562 duality_gap = 0.011537390251222896 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 13 │ 0 │ 11 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.22E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000045432560507 max_dual_value = 0.9885986943178562 duality_gap = 0.011537390251222896 [ Info: rank doubled, newrank is 2. ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 14 │ 5 │ 16 │ 8.61E-01 │ 7.09E-01 │ 2.00E+00 │ 5.00E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.7093435877036496 max_dual_value = 0.8644703157590461 duality_gap = -0.218690534100106 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 15 │ 2 │ 18 │ 9.99E-01 │ 1.02E+00 │ 2.00E+00 │ 2.50E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0220813845825503 max_dual_value = 0.9293806869849868 duality_gap = 0.09974459217384295 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 16 │ 1 │ 19 │ 1.00E+00 │ 9.76E-01 │ 2.00E+00 │ 1.25E-01 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9757741827693915 max_dual_value = 1.0043870725502784 duality_gap = -0.0293232699595302 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 17 │ 2 │ 21 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 6.25E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0030684483177195 max_dual_value = 1.0043870725502784 duality_gap = -0.0013145904796132478 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 18 │ 2 │ 23 │ 1.00E+00 │ 9.96E-01 │ 2.00E+00 │ 3.12E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9955349629273424 max_dual_value = 1.0055777024802672 duality_gap = -0.01008778187296847 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 19 │ 2 │ 25 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.56E-02 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0015712769804004 max_dual_value = 1.0055777024802672 duality_gap = -0.004000140171696688 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 20 │ 2 │ 27 │ 1.00E+00 │ 9.99E-01 │ 2.00E+00 │ 7.81E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9993927644562673 max_dual_value = 1.0055777024802672 duality_gap = -0.006188696020192704 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 21 │ 2 │ 29 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 3.91E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0004945729544164 max_dual_value = 1.0055777024802672 duality_gap = -0.005080616790194698 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 22 │ 2 │ 31 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 1.95E-03 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 0.9997744799942389 max_dual_value = 1.0055777024802672 duality_gap = -0.0058045315240111165 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 23 │ 4 │ 35 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 9.77E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted var.obj[] = 1.0000469442614395 max_dual_value = 1.0055777024802672 duality_gap = -0.005530498593655887 ┌─────────┬────┬───────┬─────────┬──────────┬──────────┬──────────┬──────────┬── │ dataset │ T │ Iterₜ │ TotIter │ ℒ │ pobj │ σ │ ηₜ │ ⋯ ├─────────┼────┼───────┼─────────┼──────────┼──────────┼──────────┼──────────┼── │ │ 23 │ -1 │ 35 │ 1.00E+00 │ 1.00E+00 │ 2.00E+00 │ 9.77E-04 │ ⋯ └─────────┴────┴───────┴─────────┴──────────┴──────────┴──────────┴──────────┴── 5 columns omitted ========================================================================================================================= End of SDPLRPlus.jl ========================================================================================================================= Test Summary: | Pass Total Time Minimum Bisection | 1 1 2.0s 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 19.4s [ 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 0.7s [ 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 4.2s Testing SDPLRPlus tests passed Testing completed after 149.69s PkgEval succeeded after 249.53s