摘要
针对汽车零部件循环取货的特点,为缩短零部件取货时间、提高车辆装载率,在循环取货过程中考虑实际车辆路径约束和三维装载约束条件,构建三维装载约束下零部件循环取货路径优化模型,设计了遗传禁忌算法与车辆装载检验算法相结合的求解算法.通过实例计算得出循环取货路线,并与传统遗传算法进行了比较,结果表明了该算法的有效性.
According to the characteristics of milk-run in automotive parts supply logistics, the optimization model of Vehicle Routing Problem with Three Dimensional Loading Constraints（3L-CVRP）in the process of milk-run is set up, combining vehicle routing constraints and three-dimensional loading constraints, in order to shorten the pickup time and improve the vehicle loading rate. Then, a hybrid algorithm-which combines Genetic-Tabu Search algorithm （GATS） with vehicle loading test algorithm is designed to solve the model. Finally, a simulation results output the milk-run routes, which indicates the effectiveness of the refined algorithm compared to the traditional GA algorithm.
出处
《武汉理工大学学报（交通科学与工程版）》
2015年第6期1161-1165,共5页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
关键词
循环取货
路径优化
三维装载
遗传禁忌算法
milk-run
vehicle routing problem
3D loading problem
genetic-tabu search algorithm （GATS）
