仓库缓存区大小与AGV数量协同优化研究
Study on the Collaborative Optimization of Warehouse Buffer Size and AGV Quantity
刘瀚松 1马云峰1
作者信息
- 1. 武汉科技大学管理学院，武汉，430065
- 折叠
摘要
为解决传统地堆式半自动化仓库出入库节拍不匹配、设备双向等待的效率问题，契合绿色物流发展需求，本文开展仓库缓存区大小与AGV数量的协同优化研究。通过分析二者在出入库作业中的交互机制，构建兼顾作业延误时间与能耗的双目标混合整数规划模型，引入能耗权重系数协调双目标优化优先级。基于Python的SimPy库搭建离散事件仿真模型，设计多组实验，模拟不同作业负荷、品类异质性、设备配置工况下的仓库作业过程。实验结果表明，缓存区容量与AGV数量存在显著替代互补效应，AGV投入呈边际效益递减规律，中等负荷下最优投入临界点为8~10台，混合人机智能配置模式可实现作业效率、资源利用率与综合成本的最优平衡。本研究明确了不同工况下二者的最优组合方案，验证了模型有效性，为传统地堆式仓库半自动化转型提供量化决策依据，丰富了仓储系统协同优化研究体系。
Abstract
To solve the efficiency problems of mismatched inbound and outbound beats and bidirectional equipment waiting in traditional bulk-stacking semi-automated warehouses, while meeting the needs of green logistics development, this paper carries out research on the coordinated optimization of warehouse buffer zone size and AGV quantity. By analyzing the interaction mechanism between the two in inbound and outbound operations, a dual-objective mixed-integer programming model considering both operation delay time and energy consumption is constructed, and an energy consumption weight coefficient is introduced to coordinate the priority of dual-objective optimization. Based on the SimPy library of Python, a discrete event simulation model is built, and multiple sets of experiments are designed to simulate the warehouse operation process under different operating loads, category heterogeneity, and equipment configuration conditions. The experimental results show that there is a significant substitution and complementary effect between buffer zone capacity and AGV quantity, the AGV input presents an obvious law of diminishing marginal returns, the optimal input critical point under medium load is 8~10 units, and the hybrid human-machine intelligent configuration mode can achieve the optimal balance among operation efficiency, resource utilization rate and comprehensive cost. This study clarifies the optimal combination scheme of the two under different working conditions, verifies the effectiveness of the constructed model, provides aquantitative decision-making basis for the semi-automated transformation of traditional bulk-stacking warehouses, and enriches the research system of coordinated optimization of warehousing systems.关键词
缓存区容量/协同优化/离散事件仿真Key words
Buffer Capacity/Collaborative Optimization/Discrete Event Simulation3引用本文复制引用
刘瀚松,马云峰.仓库缓存区大小与AGV数量协同优化研究[EB/OL].(2026-03-27)[2026-03-28].http://www.paper.edu.cn/releasepaper/content/202603-266.学科分类
自动化技术、自动化技术设备
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