The split delivery vehicle routing problem with time windows and three-dimensional loading constraints

车辆路径问题 计算机科学 数学优化 布线(电子设计自动化) 遗传算法 数学 计算机网络
作者
Miao Yan,Libing Chu,Xue Wu
出处
期刊:Journal of Industrial and Management Optimization [American Institute of Mathematical Sciences]
卷期号:20 (2): 786-807
标识
DOI:10.3934/jimo.2023102
摘要

This paper presents complex variants of the vehicle routing problem: the Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints (3L-VRPTW) and the Split Delivery Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints (3L-SDVRPTW). The difference between the two problems is whether a customer can be visited in two or more tours. Under the conditions of satisfying customer demands and loading constraints, the 3L-VRPTW model and the 3L-SDVRPTW model are constructed with the aim of minimizing transportation costs. To efficiently solve the above problems, a two-layer method is proposed in this study, including a routing stage and a packing stage. The Adaptive Large Neighborhood Search algorithm based on the Metropolis criterion is used to obtain the vehicle routing. The genetic algorithm is used to solve the packing stage, ensuring that the goods are packed in a way that minimizes pre-movements. The proposed algorithms are tested on different instances, verifying their effectiveness. Additionally, numerical experiments are conducted using instances with different customer distributions. The results show that when customers are located in multiple small areas, split delivery it distribution can significantly reduce penalty costs and be more economical.

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