车辆路径问题研究进展
Research Progress of Vehicle Routing Problem

蒋华伟 ^1,2 郭陶 ^1,2 ^* 杨震 ^1,2

文摘	车辆路径作为经典的组合优化问题一直是研究的热点与难点,无论是在应急管理工作还是物流配送中,对它的合理规划都至关重要.为了今后更好地开展相关工作,本文回顾了精确算法、启发式算法和机器学习算法在车辆路径优化问题中的研究进展,并基于Solomon标准数据集对六种经典算法的求解性能进行了比较分析;分别从局部最优和收敛速度间的平衡关系、个体评价函数、动态车辆路径问题以及机器学习算法在车辆路径问题中的应用等四个方面对其发展趋势进行了展望.
其他语种文摘	As a classical combinatorial optimization problem, vehicle routing has always been a hot and difficult research topic. It is very important to make reasonable planning for it in both emergency management and logistics distribution. In order to better carry out related work in the future, this paper reviewed the research progress of exact algorithm, heuristic algorithm, and machine learning algorithm in vehicle routing optimization problem. Then the comparisons of the performance of six classical algorithms were conducted based on Solomon standard data set. The development trend was prospected from the aspects of balance relationship between the local optimum and the convergence speed, individual evaluation function, dynamic vehicle routing problem, and the application of machine learning algorithms in the vehicle routing problem.
来源	电子学报 ,2022,50(2):480-492 【核心库】
DOI	10.12263/DZXB.20201154
关键词	车辆路径优化 ; 启发式算法 ; 精确算法 ; 机器学习
地址	1. 河南工业大学, 粮食信息处理与控制教育部重点实验室, 河南, 郑州, 450001 2. 河南工业大学信息科学与工程学院, 河南, 郑州, 450001
语种	中文
文献类型	综述型
ISSN	0372-2112
学科	自动化技术、计算机技术
基金	河南省自然科学基金
文献收藏号	CSCD:7195161