Research Article

An Improved Differential Evolution Algorithm for a Multicommodity Location-Inventory Problem with False Failure Returns

Table 7

Lingo 11 versus DE versus IDE.

InstanceLingo 11DEIDE(T1-T2) / T1
O.V.CPU Time O.V.O.V.OS RatioCPU TimeS.D.O.V.O.V.OS RatioCPU Time S.D.
(S)(Best)(Mean)(S) - T1(Best)(Mean)(S) - T2

2052698758066987580.306997722.0821/300.140.016987580.306987580.3030/300.140.01-3.95%
3103555101510355509.0110358913.9826/300.340.0510355509.0110355509.0130/300.350.03-2.63%
4134874402713487441.5513488007.0129/300.650.0513487441.5513487441.5530/300.670.05-3.08%

4062125987105312598709.0412608013.3916/301.010.0612598709.0412598750.7429/300.890.0411.68%
31864200013518642000.9118643688.3426/302.710.0818642000.9118642000.9130/302.500.087.71%
42436794026324367942.6624368298.6726/305.710.1424367942.6624367942.6630/305.190.109.02%

50532331392012323313920.9323316057.8426/304.850.3223313920.9323313920.9330/305.030.21-3.68%
62301793022923017934.3723018947.5627/306.780.1623017934.3723017934.3730/306.050.1210.76%
71947118032619471179.2919471323.4528/309.570.1719471179.2919471179.2930/307.450.1622.14%

70633165238047231652384.4531652401.0829/3016.170.5031652384.4531652384.4530/3016.260.60-0.56%
730150360139430150355.8430150535.4127/3021.510.4730150355.8430150355.8430/3018.280.4214.99%
828295930199328295927.3328296407.7525/3022.890.4328295927.3328295939.6029/3020.850.538.92%

80822193977072121939767.6621939991.6528/3013.280.2421939767.6621939767.6630/3012.050.319.31%
332943770297432943770.2232943973.2429/3041.511.1532943770.2232943770.2230/3035.760.7213.83%
443234620>360043234618.5543234779.1529/3091.601.8443234618.5543234618.5530/3074.051.3519.15%

1008339081930>360039081579.9339081760.6628/30115.952.0739081579.9339081579.9330/3069.931.4539.69%
938614670>360039767341.7140015199.700/30102.180.9038614396.0738614592.7529/3083.841.7217.95%
1036450520>360037621661.9637827792.610/30124.760.7436450173.5736450173.5730/3088.872.7428.76%