基于循环取货的汽车零部件入厂物流路径优化研究  

Research on Optimization of Inbound Logistics Path for Auto Parts Based on Milk-run

作　　者：孙慧 王学敏 孙丙琦 SUN Hui;WANG Xuemin;SUN Bingqi(Transportation College,Shandong University of Science and Technology,Qingdao 266590,China)

机构地区：[1]山东科技大学交通学院,山东青岛266590

出　　处：《物流科技》2023年第19期18-21,共4页Logistics Sci-Tech

摘　　要：由于汽车零部件入厂物流在总物流成本中占比较大,所以国内外学者不断提出多种汽车零部件入厂物流优化问题和解决方法以降低物流成本。文章基于循环取货的要求设计数学模型,并根据问题的特点来设计遗传算法中编码、适应度函数、初始种群等进行求解,最后,结合相关案例以及模型算法,使用MATLAB进行求解,从而得到最优路径。通过对数据结果的分析表明,循环取货能大幅降低物流成本,实现准时化生产;文章设计的数学模型和构造遗传算法进行求解是可行的,能高效地解决路径规划问题。Because the logistics of automobile parts entering the factory is relatively large in total logistics costs,scholars at home and abroad have continued to propose a variety of automotive component logistics optimization problems and solutions to reduce logistics costs.This article is based on the requirements of milk-run to design mathematical models,and designed the coding,adaptation function,initial population,etc.in the genetic algorithm according to the characteristics of the problem.Finally,combined with relevant cases and model algorithms to solve unexpected path.According to the analysis of data results,milk-run can significantly reduce logistics costs and achieve timely production;it is feasible to solve the mathematical model and constructing genetic algorithm designed in this article,which can efficiently solve path planning problems.

关 键 词：循环取货 入厂物流 车辆路径优化 遗传算法 

分 类 号：F252.14[经济管理—国民经济]