Research Article

A Novel Harmony Search Algorithm Based on Teaching-Learning Strategies for 0-1 Knapsack Problems

Table 3

The result of 1-dimensional (weight versus value) knapsack problems.

ProblemD Target weightTotal weight Total valuesOptimal resultAlgorithmOutcomesRuntime
WorstMeanBestStd

KP115375 741.917262.9963481.069HS314.9297423.191481.06967.921610.169532
NGHS481.069481.069481.069 E  0.173909
EHS481.069481.069481.069 E  0.814028
ITHS437.9345472.4424481.06919.29050.447476
HSTL481.069481.069481.069 E  0.330757

KP2231000019428193099767HS9747976097675.5335960.313597
NGHS97679767976700.305331
EHS96439751.6976722.645091.595463
ITHS97569765.797672.6411860.790986
HSTL97679767976700.585312

KP320878 109810851024HS924987.4102440.3955440.254834
NGHS10241024102400.245683
EHS10181022.810242.68328161.274226
ITHS10181022.810242.68328160.654352
HSTL10241024102400.485799

KP44015374140491149HS7861109.41149113.749412.51123
NGHS11381147.911493.47850512.72128
EHS7861109.41149113.749415.64561
ITHS7861112.71149114.790713.6885
HSTL11381147.911493.47850513.29233

KP510027 1360349651173HS11721172.511730.50854837.14283
NGHS11721172.63311730.49013337.22416
EHS11721172.56711730.50400753.20237
ITHS11721172.56711730.50400741.50243
HSTL11721172.911730.30512937.11053

KP6100004313493543011792unknownHS479549415338228.204952902.844
NGHS59766270.46363165.438211881.969
EHS47974929.8501494.09941616979.43
ITHS48994960.6506472.0818985047.957
HSTL63186474.46730185.71561506.648

KP710000176532650330062063406unknownHS10686281070926.510732253250.56994526.0894
NGHS11265841127050.51127517659.730635060.0062
EHS10414351043733.510460323250.56995435.1693
ITHS1124261112938911345177252.08714555.54
HSTL1193743119452411953041103.7943326.1473

KP811000100000055269812263955unknownHS529153532801.85373533001.164610633.825
NGHS738654762855.479899126865.40411912.341
EHS480038486268.84906274481.061613084.292
ITHS7952028009088071644864.542410785.623
HSTL9406569447809478502630.1089606.735