A decomposition based memetic algorithm for multi-objective vehicle routing problem with time windows
A decomposition based memetic algorithm for multi-objective vehicle routing problem with time windows
复制标题
具有时间窗的多目标车辆路径问题的基于分解的模因算法
DOI：
10.1016/j.cor.2015.04.009
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发表时间：
2015-10
影响因子：
4.6
通讯作者：
Xiaodong Li
中科院分区：
文献类型：
--
作者：
Yutao Qi;Zhanting Hou;He Li;Jianbin Huang;Xiaodong Li
基于分解的多目标进化算法（MOEA/D）为求解多目标优化问题提供了一个很好的算法框架。它将目标问题分解为一组标量子问题，并同时进行优化。MOEA/D以其简单、优异的性能得到了广泛的研究和应用。然而，对于求解带时间窗的多目标车辆路径问题（MO-VRPTW）， MOEA/D算法面临着许多子问题存在重复最优解的难题。众所周知，MO-VRPTW是一个具有挑战性的问题，并且很少有帕累托最优解。为了解决这一问题，本文设计了一种新的选择算子，以提高处理MO-VRPTW的原始MOEA/D。此外，在改进算法中引入了三种局部搜索方法。实验结果表明，该算法对所罗门问题具有较强的竞争力。特别是对于具有较长时间窗的实例，该算法可以获得比其他算法更多样化的非支配解集。进一步的分析也证明了所提出的选择算子的有效性。
Multi-objective evolutionary algorithm based on decomposition (MOEA/D) provides an excellent algorithmic framework for solving multi-objective optimization problems. It decomposes a target problem into a set of scalar sub-problems and optimizes them simultaneously. Due to its simplicity and outstanding performance, MOEA/D has been widely studied and applied. However, for solving the multi-objective vehicle routing problem with time windows (MO-VRPTW), MOEA/D faces a difficulty that many sub-problems have duplicated best solutions. It is well-known that MO-VRPTW is a challenging problem and has very few Pareto optimal solutions. To address this problem, a novel selection operator is designed in this work to enhance the original MOEA/D for dealing with MO-VRPTW. Moreover, three local search methods are introduced into the enhanced algorithm. Experimental results indicate that the proposed algorithm can obtain highly competitive results on Solomon׳s benchmark problems. Especially for instances with long time windows, the proposed algorithm can obtain more diverse set of non-dominated solutions than the other algorithms. The effectiveness of the proposed selection operator is also demonstrated by further analysis.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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DOI：
10.1016/j.amc.2006.01.059
发表时间：
2006-10
期刊：
Appl. Math. Comput.
影响因子：
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作者：
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通讯作者：
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DOI：
10.1109/icsmc.2011.6083675
发表时间：
2011-11
期刊：
2011 IEEE International Conference on Systems, Man, and Cybernetics
影响因子：
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作者：
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通讯作者：
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