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A HYBRID MULTI-OBJECTIVE GENETIC ALGORITHM ROUTING PROBLEM

机译：混合多目标遗传算法的路由问题

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摘要

Providing a satisfying delivery service is an important way to maintain the customers' loyalty and further expand profits for manufacturers and logistics providers. Considering customers' preferences for time windows, a bi-objective time window assignment vehicle routing problem has been introduced to maximize the total customers' satisfaction level for assigned time windows and minimize the expected delivery cost The paper designs a hybrid multi-objective genetic algorithm for the problem that incorporates modified stochastic nearest neighbour and insertion-based local search. Computational results show the positive effect of the hybridization and satisfactory performance of the meta-heuristics. Moreover, the impacts of three characteristics are analysed including customer distribution, the number of preferred time windows per customer and customers' preference type for time windows. Finally, one of its extended problems, the bi-objective time window assignment vehicle routing problem with time-dependent travel times has been primarily studied.
机译：提供令人满意的送货服务是维持客户忠诚度并进一步扩大制造商和物流提供商利润的重要途径。考虑到客户对时间窗的偏好，引入了双目标时间窗分配车辆路径问题，以最大化分配时间窗的总客户满意度，并最小化预期交付成本。这个问题包含修改后的随机最近邻和基于插入的本地搜索。计算结果表明了杂交的积极效果和令人满意的元启发式方法性能。此外，分析了三个特征的影响，包括客户分布，每个客户的首选时间窗口数以及客户对时间窗口的偏好类型。最后，主要研究了它的扩展问题之一，即与时间有关的双目标时间窗分配车辆路径问题。

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