Research Article
A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment
Table 4
Optimal objective function values of two algorithms.
| Instance name | Algorithm | Maximum | Minimum | Mean | Standard deviation | Coefficient of variation |
| Perl 183-12×2 | HGSAA | 740420 | 157810 | 502684 | 176218.7 | 0.350555 | GA | 1322000 | 219800 | 660282 | 234416.0 | 0.355024 | Gaskell 67-22×5 | HGSAA | 1718000 | 1071600 | 1432110 | 213118.8 | 0.148815 | GA | 3146500 | 1506200 | 2170660 | 553894.4 | 0.255173 | Gaskell 67-36×5 | HGSAA | 3635500 | 1877000 | 2879510 | 561628.4 | 0.195043 | GA | 3836900 | 2219400 | 2886460 | 582830.7 | 0.201919 | Perl 183-55×15 | HGSAA | 4120700 | 3606800 | 3985110 | 152566.1 | 0.038284 | GA | 4307000 | 3755100 | 4090590 | 185978.4 | 0.045465 | Christofides 69-75×10 | HGSAA | 5562400 | 4290900 | 4826600 | 394532.4 | 0.081741 | GA | 6359300 | 4859800 | 5418878 | 525869.4 | 0.097044 | Perl 83-85×7 | HGSAA | 6529200 | 5050500 | 5693300 | 531113.4 | 0.093287 | GA | 7057200 | 5545800 | 6283210 | 428004.8 | 0.068119 | Christofides 69-100×10 | HGSAA | 5978900 | 5074600 | 5592260 | 332403.7 | 0.05944 | GA | 6177500 | 5211900 | 5792190 | 354180.4 | 0.061148 |
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