Research Article

A New Moth-Flame Optimization Algorithm for Discounted {0-1} Knapsack Problem

Table 4

Comparison of PSO1, PSO2, SecEGA, MFO1, and MFO2 on SDKP1–SDKP10.

InstanceOPTAlgorithmBestAverageWorstStdDevGapRank

SDKP194459PSO1942199387493489184.333.94
PSO2942059399993703130.534.13
SecEGA89 7698883287463594.96.05
MFO194286942749425812.634.51
MFO294286942229412143.234.42

SDKP2160805PSO1160280159531158810360.134.94
PSO2160090159617159030307.435.03
SecEGA153 821152059150753489.45.45
MFO115998015989515980047.335.21
MFO215984015966715939093.935.02

SDKP3238248PSO1237340236389235320440.20.73
PSO2237300236428235620371.40.71
SecEGA224 997223580221918543.46.25
MFO123653023640423631051.80.72
MFO2236140235855235600128.80.44

SDKP4340027PSO1337960337013335880585.019.31
PSO2337860336811335890508.319.23
SecEGA318 510315513313 747851.17.25
MFO133698033686533680039.019.22
MFO2336390335989335730172.918.94

SDKP5463033PSO1459780458216456130728.536.53
PSO2459420458086456840615.136.54
SecEGA420 238416964413 9331291.710.05
MFO146019046009646001045.537.11
MFO2459240458554458240225.436.62

SDKP6466097PSO1462350460874459340677.11.92
PSO2462000460989459690602.61.91
SecGA430 738427304425 5041031.18.35
MFO146100046086246075064.31.93
MFO2460060459245458780226.81.54

SDKP7620446PSO16145106127466103601059.225.34
PSO2614780612902610930928.125.33
SecEGA561 224556083552 0071926.310.45
MFO161590061575661563069.225.91
MFO2613930613268612870281.125.42

SDKP8670697PSO1663730661988659770984.424.04
PSO2664250662529660340992.724.12
SecEGA611 644606263603 7741446.99.65
MFO166475066459066445076.024.51
MFO2662910662053661640303.524.03

SDKP9739121PSO17318307302837277701058.938.33
PSO27323207306197285701060.138.32
SecEGA674 885667900664 5801614.09.65
MFO173163073150273136068.338.51
MFO2728790728306727650315.537.94

SDKP10765317PSO1756580755021753220806.229.92
PSO27574307547987524701402.829.93
SecEGA708 935695557691 9942956.19.15
MFO1756190755966755650120.730.11
MFO2753740753027752270336.629.64