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中国工业与应用数学学会会刊
主管：中华人民共和国教育部
主办：西安交通大学
ISSN 1005-3085  CN 61-1269/O1
工程数学学报

工程数学学报 ›› 2025, Vol. 42 ›› Issue (5): 823-844.doi: 10.3969/j.issn.1005-3085.2025.05.003cstr: 32411.14.cjem.CN61-1269/O1.2025.05.003

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基于雪佛龙仓储布局的拣选路径优化研究

柳虎威1,  王  繁2,  赵俊辉3,  杨江龙2,  周   丽1   

  1. 1. 北京经理学院临空经济管理学院，北京 100102

    2. 北京物资学院信息学院，北京 101149

    3. 北京理工大学管理学院，北京 100081
  • 收稿日期:2022-09-04 接受日期:2023-08-21 出版日期:2025-10-15 发布日期:2025-12-15
  • 基金资助:
    国家社会科学基金 (24FGLB047)；2025年度山西省高质量发展研究课题 (SXGZL2025084)；北京经理学院科技英才支持计划资助项目.

Optimization of Picking Routing Strategies Based on the Chevron Warehouse Layout Design

LIU Huwei1,  WANG Fan2,  ZHAO Junhui3,  YANG Jianglong2,  ZHOU Li1   

  1. 1. School of Airport Economy Management, Beijing Institute of Economics and Management, Beijing 100102

    2. School of Information, Beijing Wuzi University, Beijing 101149

    3. School of Management, Beijing Institute of Technology, Beijing 100081
  • Received:2022-09-04 Accepted:2023-08-21 Online:2025-10-15 Published:2025-12-15
  • Supported by:
    The National Social Science Foundation of China (24FGLB047); the High-quality Development Research Project of Shanxi Province in 2025 (SXGZL2025084); the Science and Technology Talent Support Program of Beijing Institute of Economics and Management.

摘要：

为了提升现代仓储系统中的拣选作业效率，基于改进型布局设计中的雪佛龙仓储布局，根据其特点，构建了拣选路径行走距离的计算模型，以遗传算法、布谷鸟搜索算法、蚁群算法三种智能算法作为寻优途径来改善订单拣选过程中的路径优化问题，并对以上算法进行了仿真验证，同时与S-shape和Return两种启发式路径策略进行比较。实验结果表明，当订单拣选中需访问的货位数量为10时，三种算法均能实现对S-shape和Return两种策略的优化；随着待拣选货位数量增加至20和40，三种算法对S-shape策略的优化逐步失效；对于Return策略，随着待拣选货位数量增加至30，遗传算法失效，而布谷鸟搜索算法和蚁群算法均实现较好效果，但前者在运行时间方面更具有优势。

关键词: 雪佛龙仓储布局, 拣选路径优化, 智能算法, 启发式路径策略

Abstract:

To enhance the picking efficiency in modern warehousing systems, this paper is based on the improved layout design of the Chevron warehousing layout. According to its characteristics, a calculation model for the walking distance of picking paths is constructed. Genetic algorithm (GA), cuckoo search (CS) algorithm, and ant colony algorithm (ACO) are utilized as optimization approaches to improve the path optimization problem in order picking processes. These algorithms are simulated and compared with two heuristic path strategies, namely {S-shape} and {Return}. The experimental results demonstrate that when the number of locations to be accessed in order picking is 10, all three algorithms can optimize both {S-shape} and {Return} strategies. As the number of locations increases to 20 and 40, the optimization of {S-shape} strategy gradually becomes ineffective for all three algorithms. For the {Return} strategy, when the number of locations reaches 30, the GA weakens, while the CS algorithm and ACO achieve good results. However, the former has an advantage in terms of runtime.

Key words: Chevron warehouse layout, picking routing optimization, intelligent algorithms, heuristic routing strategies

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