基于改进遗传算法的路径规划问题应用  

Route Planning Problem Application Based on Improved Genetic Algorithm

作　　者：辛钢 宋少忠 张慧 安毅 XIN Gang;SONG Shaozhong;ZHANG Hui;AN Yi(Engineering Institute,Jilin Business and Technology College,Changchun 130507,China;School of Data Science and Artificial Intelligence,Jilin Engineering Normal University,Changchun 130052,China;School of Electrical and Information Engineering,Jilin Engineering Normal University,Changchun 130052,China;School of Information Technology Department,Changchun Automobile Industry Institute,Changchun 130013,China)

机构地区：[1]吉林工商学院工学院,长春130507 [2]吉林工程技术师范学院数据科学与人工智能学院,长春130052 [3]吉林工程技术师范学院电气与信息工程学院,长春130052 [4]长春汽车工业高等专科学校信息技术学院,长春130013

出　　处：《吉林大学学报（信息科学版）》2022年第6期946-953,共8页Journal of Jilin University（Information Science Edition）

基　　金：吉林省教育厅“十二五”科学技术研究基金资助项目(2012377,2013394)。

摘　　要：信息化赋能传统物流行业的迭代升级,为解决由于汽车制造业独有的物流特点带来的运输难题,使循环取货速度提升、成本费用降低及物流车辆造成城市内部交通压力得到缓解,以汽车厂A在城市Q本地循环取货实际运输需求为基础,设计了基于改进的遗传算法用于汽车零部件运输的智能路径规划方法。利用循环物流过程中当月零部件需求量、供应商订单详情、选配运输车辆容载率、单车器具体积占比、时间窗需求等耦合性因素,使用大规模邻域搜索算法改进遗传算法,求解出应用Solomon数据算例的最优路径并于遗传算法相比较和厂A与供应商间实际运输需求的最优配送方案线路。实验结果表明,该方法在性能上具有显著优越性,数值仿真结果阐明了该方法的适用性和优化过程中的收敛情况。Information enables the iterative upgrading of traditional logistics industry.In order to solve the transportation problems caused by the unique logistics characteristics of automobile manufacturing industry,it considers the improvement of the speed for milk-run,reducing the cost and alleviation the traffic pressure caused by logistics vehicles in the city,based on the actual transportation demands of milk-run of automotive equipment manufacturer A in city Q.An intelligent path planning method for automobile parts transportation based on improved GA(Genetic Algorithm)algorithm is designed.The genetic algorithm is improved by using the coupling factors such as the demand of parts and components in the current month,the details of supplier orders,the capacity rate of optional transportation vehicles,the volume proportion of single vehicle appliances,and the demand of time window in the process of milk-run.In this way,the optimal path using Solomon data example is solved and compared with genetic algorithm,and the optimal distribution scheme for solving the actual transportation demands between A and the suppliers.The experimental results show that the method has some advantages in performance.The numerical simulation results illustrate the applicability of the method and the convergence in the optimization process.

关 键 词：循环物流 时间窗需求 车辆容载率 最优配送方案 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]