用户驱动冷链中心选择-时变路径时空聚类优化
User-driven spatiotemporal clustering optimization for cold chain center selection with time-varying paths
摘要
Abstract
[Purposes]This study explores the problem of fresh cold chain center selection and routing under the conditions of differentiated customer demands and time-varying traffic.It aims to provide decision-making support for precise services targeting different customer segments,distribution center selection,and time-varying routing planning.[Methods]To minimize the total system cost(including vehicle costs,distribution center operation costs,time window penalty costs,spoilage loss costs,fuel consumption costs,and carbon emission costs),the model incorporated constraints reflecting the demands of different customer groups based on customer profile,time-varying speeds,and vehicle load capacities.A two-stage heuristic algorithm was developed for simulation experiments:Stage 1 allocated customers to distribution centers using a heuristic selection algorithm based on spatiotemporal distance.Stage 2 optimized routes using a genetic algorithm(GA).[Findings]The user profile-driven differentiation strategy significantly improves service quality,with the core customer group receiving optimal distribution services.Compared with that of the traditional genetic algorithm and the K-means clustering+genetic algorithm,the optimal cost of the two-stage heuristic algorithm is reduced by 9.15%and 12.61%,respectively.Meanwhile,the scheme under time-varying speed can better balance cost and timeliness than that under fixed speed,with the total driving time and cost within a reasonable range.[Conclusions]The proposed model and two-stage algorithm provide decision-making support for fresh cold chain enterprises to implement differentiated distribution strategies.关键词
城市交通运输/冷链中心选择/用户画像/时变路径/时空聚类/遗传算法Key words
urban transportation/cold chain center selection/user profile/time-varying path/spatiotemporal clustering/genetic algorithm分类
交通工程引用本文复制引用
吴昊,于宁,孟强浩..用户驱动冷链中心选择-时变路径时空聚类优化[J].长沙理工大学学报（自然科学版）,2025,22(5):115-129,15.基金项目
安徽省教育厅自然科学研究项目(KJ2021A0480) （KJ2021A0480）
安徽省高校自然科学研究重大项目(2023AH040045) （2023AH040045）
安徽财经大学研究生科研创新基金项目(ACYC2023045) （ACYC2023045）
2023年中国高校产学研创新基金项目(2023RY003) （2023RY003）
合肥市日煜节能科技有限公司企业委托项目(2023001) Project(KJ2021A0480)supported by the Natural Science Research Project of Anhui Provincial Department of Education （2023001）
Major Project of Natural Science Research for Universities of Anhui Province(2023AH040045) （2023AH040045）
Graduate Scientific Research Innovation Foundation Project of Anhui University of Finance and Economics(ACYC2023045) （ACYC2023045）
2023 China University Industry-University-Research Innovation Fund Project(2023RY003) （2023RY003）
Enterprise-Commissioned Research Project Sponsored by Hefei City Yu Energy Science and Technology Co.,Ltd.(2023001) （2023001）
