井冈山大学学报（自然科学版）2026，Vol.47Issue(2)：82-89,8.DOI:10.3969/j.issn.1674-8085.2026.02.010
基于分布鲁棒优化的多隔室冷链车辆路径规划模型研究
Research on multi-compartment cold chain vehicle routing planning model based on distributionally robust optimization
摘要
Abstract
This study investigates the vehicle routing problem for multi-compartment cold chain vehicles transporting refrigerated and frozen goods.First,considering the dual uncertainties of customer demand and environmental temperature,as well as compartment capacity constraints affecting routing decisions and refrigeration energy consumption,a distributionally robust optimization model with fuzzy chance constraints is formulated to minimize total costs.Second,a hybrid distributionally robust optimization method integrating moment information and Wasserstein distance is proposed to construct ambiguity sets for demand and temperature uncertainties.The original model is transformed into computationally tractable integer second-order cone programming and mixed-integer linear programming formulations.Finally,the Beluga Whale optimization algorithm is employed to identify optimal routes.Comparative simulations with other uncertainty-handling methods demonstrate that the distributionally robust optimization approach exhibits stronger robustness,avoids extreme conservatism,and achieves better cost-effectiveness in addressing uncertainty.关键词
分布鲁棒优化/多隔室冷链车辆/不确定性/路径规划/白鲸优化算法Key words
distributionally robust optimization/multi-compartment cold chain vehicles/uncertainty/path planning/Beluga Whale optimization分类
交通工程引用本文复制引用
郭海峰,路航..基于分布鲁棒优化的多隔室冷链车辆路径规划模型研究[J].井冈山大学学报（自然科学版）,2026,47(2):82-89,8.基金项目
辽宁省教育厅高等学校基本科研项目(LJKMZ20220616) （LJKMZ20220616）
