Research Article

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

Table 3

Comparison of PSO1, PSO2, SecEGA, MFO1, and MFO2 on IDKP1–IDKP10.

InstanceOPTAlgorithmBestAverageWorstStdDevGapRank

IDKP170106PSO1694716898068252288.01.64
PSO2695306911768376237.21.43
SecEGA68 6636800067 369328.43.05
MFO17010670106701060.00.01
MFO27010670104700904.90.02

IDKP2118268PSO1116710116212115370354.21.74
PSO2117200116516115700337.31.53
SecEGA114 434113385112 3077446.74.15
MFO11182680.00.01
MFO211826811825111823019.30.02

IDKP3234804PSO1234290233653232350420.40.53
PSO2234390232600232600389.60.44
SecEGA220 096217982216 313835.87.25
MFO12347702347482347407.70.01
MFO223470023454423436092.30.12

IDKP4282591PSO1280540279714277810578.11.04
PSO2280770279858279110486.71.03
SecEGA263 238260425258 922933.47.85
MFO12825902825872825705.80.01
MFO2282470282210281940132.10.12

IDKP5335584PSO1333140331595329340748.81.24
PSO2332710331896329280691.21.13
SecEGA309 573306878304 881907.28.65
MFO13355803355803355800.00.01
MFO2335280335000334780107.20.22

IDKP6452463PSO1450290449287447540681.70.74
PSO2450880449350447890683.30.73
414 090411367408 7881099.39.15
MFO14524304524154523909.70.01
MFO2451750451293450990198.30.32

IDKP7489149PSO1483180481656478830944.51.53
PSO24831704815784799101034.91.54
SecEGA451 528444316442 1331280.39.25
MFO14891504891324891209.70.01
MFO2488520487889487030288.10.32

IDKP8533841PSO15233005209395177201480.02.44
PSO25262405218445191901540.02.23
SecEGA490 494481831478 0352215.79.75
MFO15338405338255338206.30.01
MFO2533050532345531940284.30.32

IDKP9528144PSO15156805119085072101937.03.14
PSO25165505125755090901727.02.93
SecEGA489 661477001471 8483656.29.75
MFO15281405281365281207.20.01
MFO2527140526734526370205.80.32

IDKP10581244PSO15639605602145561002204.13.64
PSO25666705620005595401950.23.33
SecEGA535 541521604516 4454265.110.35
MFO15812405812335812304.50.01
MFO2580620579589578870365.00.32