Research Article
A Hybrid Genetic-Simulated Annealing Algorithm for the Location-Inventory-Routing Problem Considering Returns under E-Supply Chain Environment
Table 5
CPU time (seconds) for calculation of two algorithms.
| Instance name | Algorithm | Maximum | Minimum | Mean | Standard deviation | Coefficient of variation |
| Perl 183-12×2 | HGSAA | 0.8424 | 0.4992 | 0.65156 | 0.085708 | 0.131543 | GA | 0.9672 | 0.5304 | 0.6696 | 0.102803 | 0.153529 | Gaskell 67-22×5 | HGSAA | 1.716 | 1.092 | 1.37436 | 0.169531 | 0.123353 | GA | 2.1216 | 1.17 | 1.55688 | 0.272075 | 0.174756 | Gaskell 67-36×5 | HGSAA | 3.7596 | 2.2776 | 3.2058 | 0.501429 | 0.156413 | GA | 4.8984 | 2.5584 | 3.81108 | 0.760696 | 0.199601 | Perl 183-55×15 | HGSAA | 12.0121 | 8.5957 | 9.91249 | 0.999262 | 0.100808 | GA | 12.6517 | 9.8125 | 10.91837 | 0.846487 | 0.077529 | Christofides 69-75×10 | HGSAA | 13.3225 | 10.1713 | 11.74674 | 1.162717 | 0.098982 | GA | 13.7437 | 10.2805 | 12.30382 | 1.370948 | 0.111425 | Perl 83-85×7 | HGSAA | 21.6373 | 17.0509 | 18.94194 | 1.305246 | 0.068908 | GA | 24.3518 | 17.8621 | 21.04736 | 2.279007 | 0.10828 | Christofides 69-100×10 | HGSAA | 33.2906 | 30.1859 | 31.36279 | 0.93519 | 0.029818 | GA | 33.5558 | 30.6386 | 32.21258 | 0.962075 | 0.029866 |
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