Research Article
Multi Objective Optimization of Coordinated Scheduling of Cranes and Vehicles at Container Terminals
Table 6
Comparative results for ten small size test cases solved by the MIP model and the GA method.
| No. | MIP model | Proposed GA | Deviation % | Decision variables | Optimal | CPU time | Mean | Best | CPU time |
| 1 | 132 | 471 | 180 S | 471 | 471 | 7.4 S | 0 | 2 | 176 | 775 | 1440 S | 775 | 775 | 9.6 S | 0 | 3 | 205 | 806 | 4200 S | 818 | 818 | 9.8 S | 1.49 | 4 | 226 | 1055 | 5100 S | 1065 | 1061 | 12.3 S | 0.57 | 5 | 259 | 675 | 7500 S | 689.2 | 687 | 12.4 S | 1.77 | 6 | 259 | 923 | 9000 S | 1033.5 | 1016 | 12.6 S | 10.07 | 7 | 282 | 872 | 11880 S | 921.3 | 916 | 14.8 S | 5.04 | 8 | 319 | 1064 | 12300 S | 1110.5 | 1089 | 16.8 S | 2.35 | 9 | 319 | 1154 | 15120 S | 1186.2 | 1162 | 15.3 S | 0.69 | 10* | 344 | 1137 | 27000 S | 1165.3 | 1159 | 20.3 S | 1.93 |
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The best obtained result in a limited CPU time.
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