车辆路径问题
皮卡
计算机科学
布线(电子设计自动化)
整数规划
数学优化
混合算法(约束满足)
平面图(考古学)
运筹学
工程类
算法
计算机网络
数学
随机规划
人工智能
约束规划
图像(数学)
考古
历史
约束逻辑程序设计
作者
Wenjie Liu,Yutong Zhou,Wei Liu,Jing Qiu,Naiming Xie,Xiangyun Chang,Jian Chen
标识
DOI:10.1016/j.cie.2021.107747
摘要
The vehicle routing problem with simultaneous delivery & pickup and real-time traffic information (VRPSDPTI) is a dynamic problem of combinatorial network optimisation in logistics and supply chain management. It is also a typical NP-hard problem that has plagued enterprises with reverse logistics operations for many years. The main objective of this research is to determine an optimal vehicle routing plan for the VRPSDPTI problem. To achieve this goal, a mixed integer programming (MIP) model is constructed, with the objective of minimising the total travel cycle for the VRPSDPTI problem. A hybrid algorithm of the ant colony system and virtual transformation method (ACS-VTM) is then designed to explore the vehicle routing plan for the VRPSDPTI problem; it adopts a flexible split of the time period for re-optimisation and an improved partial service policy for customer demand. Based on it, a practical case of the VRPSDPTI problem is used to verify the proposed model and algorithm. One major finding is proposed through the study of the practical case that adopting the hybrid ACS-VTM algorithm can effectively reduce the total travel cycle for the VRPSDPTI problem. The main contributions of this study are that it can provide an efficient decision tool to solve the VRPSDPTI, and can not only reduce the total travel cycle, but also improve the efficiency of vehicle utilisation.
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