系统仿真学报 ›› 2026, Vol. 38 ›› Issue (10): 2997-3014.doi: 10.16182/j.issn1004731x.joss.25-1148

• 复杂系统调度与资源配置 • 上一篇    下一篇

工业集群异构车队配置与多模态路径协同优化

肖仁鑫, 徐一帆, 陈贵升, 潘楠   

  1. 昆明理工大学 交通工程学院,云南 昆明 650500
  • 收稿日期:2025-11-21 修回日期:2025-12-29 出版日期:2026-10-31 发布日期:2026-10-20
  • 通讯作者: 潘楠
  • 第一作者简介:肖仁鑫(1978-),男,副教授,博士,研究方向为电动汽车动力系统优化控制。
  • 基金资助:
    国家自然科学基金(52562048)

Coordinated Optimization of Heterogeneous Fleet Configuration and Multimodal Routing for Industrial Clusters

Xiao Renxin, Xu Yifan, Chen Guisheng, Pan Nan   

  1. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
  • Received:2025-11-21 Revised:2025-12-29 Online:2026-10-31 Published:2026-10-20
  • Contact: Pan Nan

摘要:

针对工业集群货物运输中电动异构车队调度任务多样、能耗与运输时效强约束强的挑战,构建了一种融合异构电动车队配置与多模态路径协同的双层优化模型。考虑异构电动车队在载重-能耗-续航方面的性能耦合特性,上层在协同多模态路径与车队配置编码的基础上采用GWO优化任务拆分与车队配置;下层借助多邻域SA实现路径协同调度。仿真结果表明:异构车队与多模态路径协同优化能够降低运输综合成本26.4%、减少行驶距离7%、减少配置车辆数16.7%,车队准时性与调度可靠性明显改善。为工业集群货物闭环运输提供了可推广的技术路径。

关键词: 异构车队配置, 多模态路径, 协同优化, 多因素约束, 车队能效

Abstract:

A two-level optimization model integrating heterogeneous electric vehicle fleet configuration with multimodal path coordination is built to address the challenges in industrial cluster freight transportation involving electric heterogeneous fleet scheduling, such as diverse tasks and stringent constraints on energy consumption and delivery timeliness. Considering the performance coupling characteristics of heterogeneous electric fleets in terms of load-energy consumption-endurance, based on the coordination of multimodal paths and fleet configuration coding, the upper level employs the GWO to optimize task splitting and fleet configuration. The lower level adopts a multi-neighborhood SA algorithm to achieve path coordination scheduling. Simulation results show that the coordinated optimization of heterogeneous fleets and multimodal paths reduces the comprehensive transportation cost by 26.4%, the travel distance by 7%, and the number of configured vehicles by 16.7%, with significantly improved fleet timeliness and scheduling reliability. A generalizable technical path is provided for closed-loop freight transportation of industrial clusters.

Key words: heterogeneous fleet configuration, multimodal path, coordinated optimization, multi-factor constraints, fleet energy efficiency

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