引用本文:陈可嘉,司徒腾宽,方云飞,陈荣晖.灵活车场多类型叫车接送问题的改进模拟退火算法[J].控制理论与应用,2026,43(3):614~624.[点击复制]
CHEN Ke-jia,SITU Teng-kuan,FANG Yun-fei,CHEN Rong-hui.Improved simulated annealing algorithm for multiple depots heterogeneous dial-a-ride problem with flexible depots[J].Control Theory & Applications,2026,43(3):614~624.[点击复制]
灵活车场多类型叫车接送问题的改进模拟退火算法
Improved simulated annealing algorithm for multiple depots heterogeneous dial-a-ride problem with flexible depots
摘要点击 500  全文点击 65  投稿时间：2024-01-21  修订日期：2025-10-06
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DOI编号  10.7641/CTA.2024.40060
  2026,43(3):614-624
中文关键词  叫车接送问题  灵活车场  模拟退火  解接受策略优化  回温策略
英文关键词  dial-a-ride problem  flexible depots  simulated annealing  solution acceptance strategy optimization  re heating strategy
基金项目  国家社会科学基金项目(23BGL296)资助.
作者单位E-mail
陈可嘉 福州大学经济与管理学院 kjchen@fzu.edu.cn 
司徒腾宽 福州大学经济与管理学院  
方云飞* 福州大学经济与管理学院 yf.fang@fzu.edu.cn 
陈荣晖 福州大学经济与管理学院  
中文摘要
      面对老龄化社会和个性化交通需求的挑战,灵活车场多类型叫车接送在提供高效、便捷的交通解决方案方 面显得尤为重要.然而,灵活车场环境下车辆的异构性和调度的复杂性,使得服务优化面临巨大难题.本文提出的改 进模拟退火算法,针对这一问题,显著优化了车辆总行驶距离.该算法设计了一种基于宽容度与回温机制的解接受 策略,以及3种新的搜索算子,旨在提高算法稳定性和避免过早陷入局部最优.与CPLEX求解器和确定性退火算法 相比,本算法在多个测试实例上展现出显著优势.通过敏感性分析,研究了乘客最大行驶时间和时间窗口对算法性 能的影响,为实际的叫车接送规划提供了决策支持.
英文摘要
      Facing the challenges of an aging society and individualized transportation demands, the multiple depot s heterogeneous dial-a-ride problem with flexible depots (MDHDARP-FD) is crucial for providing efficient and conve nient transportation solutions. However, the heterogeneity of vehicles and the complexity of scheduling in flexible depots environments pose significant challenges to service optimization. This paper proposes an improved simulated annealing algorithm that significantly optimizes the total vehicle travel distance for the problem. According to the characteristics of the problem, the algorithm designs a solution acceptance strategy based on tolerance and reheating mechanisms, as well as three new search operators to enhance the algorithm’s stability and avoid premature convergence to local optimization. Compared with the CPLEX solver and the deterministic annealing algorithm, our algorithm shows significant advantages across multiple test instances. Through sensitivity analysis, the impacts of passengers’maximum ride time and time win dows on the algorithm’s performances are studied, which provides decision support for actual dial-a-ride planning.