[TambyVanderpooten] improve performance based on profiling

[odow]

x-ref #167

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 100.00%. Comparing base (6b7ae28) to head (75acbaf).
⚠️ Report is 1 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff            @@
##            master      #170   +/-   ##
=========================================
  Coverage   100.00%   100.00%           
=========================================
  Files           12        12           
  Lines         1212      1243   +31     
=========================================
+ Hits          1212      1243   +31     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[odow]

using JuMP, HiGHS, Gurobi
import MultiObjectiveAlgorithms as MOA

function solve_tamby_mokp(filename)
    lines = readlines(filename)
    p = parse(Int, lines[1])
    n = parse(Int, lines[2])
    b = parse(Float64, lines[3])
    C = collect(reduce(hcat, Float64.(x.args) for x in Meta.parse(lines[4]).args)')
    w = Meta.parse(lines[5]).args
    model = direct_model(MOA.Optimizer(Gurobi.Optimizer))
    set_attribute(model, MOA.Algorithm(), MOA.TambyVanderpooten())
    set_time_limit_sec(model, 5.0)
    @variable(model, x[1:n], Bin)
    @constraint(model, w' * x <= b)
    @objective(model, Max, C * x)
    optimize!(model)
    return (;
        solve_time = solve_time(model),
        result_count = result_count(model),
        Y = [objective_value(model; result) for result in 1:result_count(model)],
        subproblem_count = get_attribute(model, MOA.SubproblemCount()),
    )
end
filename = "/Users/odow/git/tambysatya/TamVan19/Instances/MOKP/MOKP_p-6_n-30_1.dat"
solve_tamby_mokp(filename)

Before

  344   -1.04700e+03 -1.07200e+03 -1.01600e+03 -9.44000e+02 -9.65000e+02 -1.37100e+03  4.76810e+00
  345  auxillary subproblem                                                            4.84938e+00
  346   -1.02200e+03 -1.09000e+03 -1.17600e+03 -1.01500e+03 -1.02000e+03 -1.20600e+03  4.85161e+00
  347  auxillary subproblem                                                            4.93469e+00
  348   -9.69000e+02 -1.20300e+03 -1.12400e+03 -1.00300e+03 -8.17000e+02 -1.06300e+03  4.93881e+00
--------------------------------------------------------------------------------------------------
TerminationStatus: TIME_LIMIT
ResultCount: 131
--------------------------------------------------------------------------------------------------
(solve_time = 5.017430067062378, result_count = 131, Y = [[1177.0, 1032.0, 1071.0, 885.0, 846.0, 1141.0], [1176.0, 1014.0, 1091.0, 911.0, 918.0, 1176.0], [1172.0, 1074.0, 1066.0, 923.0, 811.0, 1182.0], [1172.0, 1006.0, 984.0, 885.0, 788.0, 1192.0], [1165.0, 981.0, 1061.0, 956.0, 799.0, 1155.0], [1161.0, 1122.0, 1142.0, 933.0, 802.0, 1134.0], [1160.0, 1047.0, 1133.0, 911.0, 905.0, 1221.0], [1160.0, 979.0, 1051.0, 873.0, 882.0, 1231.0], [1159.0, 1040.0, 1089.0, 888.0, 950.0, 1179.0], [1155.0, 1021.0, 1046.0, 911.0, 847.0, 1272.0]  …  [876.0, 1040.0, 1083.0, 1116.0, 751.0, 1202.0], [872.0, 1041.0, 1135.0, 1129.0, 753.0, 986.0], [871.0, 977.0, 1213.0, 1121.0, 838.0, 1022.0], [870.0, 1067.0, 1207.0, 1122.0, 763.0, 1045.0], [865.0, 1049.0, 1170.0, 920.0, 1084.0, 1130.0], [864.0, 1132.0, 1335.0, 1001.0, 909.0, 1102.0], [845.0, 961.0, 1182.0, 935.0, 1066.0, 978.0], [840.0, 933.0, 1063.0, 945.0, 1066.0, 1051.0], [838.0, 1041.0, 1153.0, 1124.0, 759.0, 991.0], [830.0, 1079.0, 1103.0, 1098.0, 742.0, 1212.0]], subproblem_count = 348)

After

 1078   -9.47000e+02 -1.03700e+03 -1.12900e+03 -1.09900e+03 -8.19000e+02 -1.17100e+03  4.92726e+00
 1080   -1.00900e+03 -1.05900e+03 -1.15700e+03 -9.26000e+02 -1.07200e+03 -1.19500e+03  4.94397e+00
 1082   -9.98000e+02 -1.06300e+03 -1.14700e+03 -8.98000e+02 -8.94000e+02 -1.36100e+03  4.95577e+00
 1084   -9.12000e+02 -1.12700e+03 -1.14100e+03 -1.09500e+03 -7.50000e+02 -1.19900e+03  4.96765e+00
 1086   -9.44000e+02 -1.05800e+03 -1.16700e+03 -9.25000e+02 -1.08300e+03 -1.13800e+03  4.98122e+00
 1088   -9.52000e+02 -1.11100e+03 -1.32700e+03 -1.03400e+03 -8.74000e+02 -1.15300e+03  4.99674e+00
--------------------------------------------------------------------------------------------------
TerminationStatus: TIME_LIMIT
ResultCount: 293
--------------------------------------------------------------------------------------------------
(solve_time = 5.012986898422241, result_count = 293, Y = [[1177.0, 1032.0, 1071.0, 885.0, 846.0, 1141.0], [1176.0, 1014.0, 1091.0, 911.0, 918.0, 1176.0], [1172.0, 1074.0, 1066.0, 923.0, 811.0, 1182.0], [1172.0, 1006.0, 984.0, 885.0, 788.0, 1192.0], [1171.0, 1067.0, 1022.0, 900.0, 856.0, 1140.0], [1170.0, 939.0, 1066.0, 918.0, 834.0, 1114.0], [1165.0, 981.0, 1061.0, 956.0, 799.0, 1155.0], [1164.0, 974.0, 1017.0, 933.0, 844.0, 1113.0], [1161.0, 1122.0, 1142.0, 933.0, 802.0, 1134.0], [1160.0, 1047.0, 1133.0, 911.0, 905.0, 1221.0]  …  [861.0, 1021.0, 1088.0, 1085.0, 900.0, 1153.0], [854.0, 1063.0, 1297.0, 961.0, 1018.0, 1041.0], [847.0, 996.0, 1076.0, 1073.0, 741.0, 1261.0], [846.0, 1057.0, 1114.0, 1088.0, 809.0, 1209.0], [845.0, 961.0, 1182.0, 935.0, 1066.0, 978.0], [844.0, 1044.0, 1347.0, 1016.0, 891.0, 950.0], [840.0, 933.0, 1063.0, 945.0, 1066.0, 1051.0], [838.0, 1041.0, 1153.0, 1124.0, 759.0, 991.0], [833.0, 1015.0, 1066.0, 1124.0, 701.0, 1042.0], [830.0, 1079.0, 1103.0, 1098.0, 742.0, 1212.0]], subproblem_count = 1088)

We're about 3x faster