摘要
针对配送中心车型多样、客户需求动态变化且车辆行驶时间依赖配送区域路网速度变化特征的动态车辆路径问题,基于先预优化后动态调整的思想建立了以配送成本最小化为目标的两阶段优化模型.在预优化阶段,设计改进自适应遗传算法获得初始配送方案;在动态调整阶段,综合考虑客户需求变化和配送路网速度的变化,制定连续性和周期性相结合的优化策略,将问题转化为多中心车辆路径问题进行求解.通过实验分析验证了模型与算法的有效性,研究成果可丰富车辆路径问题的相关研究,为物流企业优化决策配送方案提供理论依据.
In order to effectively solve the dynamic vehicle routing problem of heterogeneous fleets,customers’ dynamic requests and real-time variations in travel times between nodes in distribution networks,a two-stage mathematical model with the goal of minimizing distribution costs was established based on the idea of pre-optimization and dynamic adjustment in this paper.In the pre-optimization stage,an improved adaptive genetic algorithm is designed to gain the initial distribution scheme;In the dynamic adjustment stage,comprehensively consider the customers’ dynamic requests and the speed of the distribution networks,formulate an optimization strategy that combines continuity and periodicity,and turn the problem into multi-depot vehicle routing problem for solution.The effectiveness of the model and algorithm is verified by example analysis.The research results can enrich the relevant research on vehicle routing problem and provide theoretical basis for logistics enterprises to optimize realistic distribution schemes.
作者
范厚明
张跃光
田攀俊
曹宇
任晓雪
FAN Houming;ZHANG Yueguang;TIAN Panjun;CAO Yu;REN Xiaoxue(Transportation Engineering College,Dalian Maritime University,Dalian 116026,China;China Waterborne Transport Research Institute,Beijing 100088,China)
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2022年第2期455-470,共16页
Systems Engineering-Theory & Practice
基金
国家社科基金应急管理体系建设研究专项(20VYJ024)。
关键词
车辆路径问题
时变路网
异型车辆
动态需求
自适应遗传算法
vehicle routing problem
time-dependent networks
heterogeneous fleets
dynamic demand
adaptive genetic algorithm
