摘要
末端配送环节对于城市物流的快速发展起着重要作用。为降低城市物流成本,本文从末端配送中的前置仓出发,在客户分类的基础上构建以最小化城市物流成本和最大化客户满意度为目标的城市物流选址-路径多目标优化模型。结合节约算法和扫描法对自适应大邻域搜索算法(AdaptiveLarge Neighborhood Search,ALNS)进行改进,并以国内某企业的末端配送为算例展开分析。结果表明:本文提出的模型对于改善城市物流规划,降低城市物流末端配送成本有着重要作用;相较于ALNS算法,改进的ALNS算法能够有效提高求解效率和解的质量。研究结果为城市物流的进一步发展提供了参考。
The terminal distribution plays an important role in the rapid development of urban logistics.In order to reduce the cost of urban logistics,this paper builds a multi-objective location-routing optimization model of urban logistics based on customer classification,which aims to minimize the cost of urban logistics and maximize customer satisfaction.The Adaptive Large Neighborhood Search algorithm is improved by combining saving algorithm and scanning method,and the terminal distribution of an enterprise is analyzed as an example.The results show that the model proposed in this paper plays an important role in improving urban logistics planning and reducing the terminal distribution cost of urban logistics.In addition,compared with the ALNS algorithm,the improved ALNS algorithm can effectively improve the solving efficiency and the quality of the solution.The results provide a reference for the further development of urban logistics.
作者
程文婧
宋瑞
刘逸凡
王辉
CHENG Wenjing;SONG Rui;LIU Yifan;WANG Hui(Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport of Beijing Jiaotong University,Beijing 100044,China)
出处
《综合运输》
2025年第8期150-156,共7页
China Transportation Review
基金
中央高校基本科研业务费专项资金资助(2024JBZX038)
中国国家铁路集团有限公司科技研究开发计划课题(P2023S006)。
关键词
公路运输经济
前置仓
选址-路径
客户分类
自适应大规模邻域搜索算法
Highway transportation economy
Front warehouse
Location-routing problem
Customer classification
Adaptive large neighborhood search algorithm
