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The improved adaptive link adjustment evolutionary algorithm for the multiple container packing problem
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DOI：10.1007/s10489-008-0155-6.png)
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Abstract
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In this paper, we propose a new version of Adaptive Link Adjustment Evolutionary Algorithm (ALA-EA) for the network optimization problems, and apply it to the multiple container packing problem (MCPP). Because the proposed algorithm uses a different encoding method from that of the original ALA-EA, we also need different decoding methods for the new algorithm. In addition, to improve the performance of the proposed algorithm, we incorporate heuristic local improvement approaches into it. To verify the effectiveness of the proposed algorithm we compare it with the existing evolutionary approaches for several instances, which are known to be extremely difficult to them. Computational tests show that the algorithm is superior to the existing evolutionary approaches and the original ALA-EA in both of the solution quality and the computational time. Moreover, the performance seems to be not affected by an instance property.
Keywords:
Evolutionary algorithm
Multiple container packing problem
Adaptive link adjustment
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APPLIED INTELLIGENCE
APPLIED INTELLIGENCEIF3.5
PREAI
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