考虑服务顺序和平衡性MOVRPTW问题的EASS-HHO算法
EASS-HO Algorithm for MOVRPTW Problems with Service Order and Balance
摘要: 考虑服务顺序和平衡性带时间窗的多目标车辆路径问题，以最小化配送成本，最小化车辆流转时间差和最大化顾客满意度为目标，构建模型。针对该模型特点，设计了一种边际采样–哈里斯·鹰算法对该模型进行求解。最后使用所罗门算例测试，结果表明：边际采样–哈里斯·鹰算法求解结果比基本哈里斯·鹰算法得到了改善。该算法求解现有文献中实例也较文献中结果更优。求解性能与其它启发式算法相比较该算法性能更高效。
Abstract: A multi-objective vehicle routing problem with time windows considering service order and balance is constructed to minimize delivery costs, minimize vehicle flow time differences, and maximize customer satisfaction. A marginal sampling Harris Eagle algorithm was designed to solve the model based on its characteristics. Finally, a Solomon example was used for testing, and the results showed that the marginal sampling Harris Eagle algorithm improved the solution results compared to the basic Harris Eagle algorithm. This algorithm also performs better in solving examples in existing literature than in literature. Compared with other heuristic algorithms, this algorithm performs more efficiently in solving problems.
文章引用：张天翼, 张惠珍, 李留留. 考虑服务顺序和平衡性MOVRPTW问题的EASS-HHO算法[J]. 运筹与模糊学, 2025, 15(5): 87-99. https://doi.org/10.12677/orf.2025.155234

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