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The vehicle routing problem with relaxed priority rules
EURO Journal on Transportation and Logistics Pub Date : 2021-05-07 , DOI: 10.1016/j.ejtl.2021.100039
Thanh Tan Doan , Nathalie Bostel , Minh Hoàng Hà

The Vehicle Routing Problem (VRP) is one of the most studied topics in Operations Research. Among the numerous variants of the VRP, this research addresses the VRP with relaxed priority rules (VRP-RPR) in which customers are assigned to several priority groups and customers with the highest priorities typically need to be served before lower priority ones. Additional rules are used to control the trade-off between priority and cost efficiency. We propose a Mixed Integer Linear Programming (MILP) model to formulate the problem and to solve small-sized instances. A metaheuristic based on the Adaptive Large Neighborhood Search (ALNS) algorithm with problem-tailored components is then designed to handle the problem at larger scales. The experimental results demonstrate the performance of our proposed algorithm. Remarkably, it outperforms a metaheuristic recently proposed to solve the Clustered Traveling Saleman Problem with d-relaxed priority rule (CTSP-d), a special case of VRP-RPR, in both solution quality and computational time.



中文翻译:

具有宽松优先级规则的车辆路径问题

车辆路径问题(VRP)是运筹学中研究最多的主题之一。在VRP的众多变体中,本研究针对具有宽松优先级规则(VRP-RPR)的VRP,在该规则中,将客户分配到几个优先级组,并且通常需要为具有最高优先级的客户提供服务,然后再向较低优先级的客户提供服务。其他规则用于控制优先级和成本效率之间的权衡。我们提出了一个混合整数线性规划(MILP)模型来提出问题并解决小型实例。然后,基于带有问题量身定制的组件的自适应大邻域搜索(ALNS)算法的元启发式方法将被设计为更大规模地处理问题。实验结果证明了该算法的性能。值得注意的是d-松弛优先级规则(CTSP- d),这是VRP-RPR的特例,在解决方案质量和计算时间上均如此。

更新日期:2021-05-18
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