高密度箱式库的订单波次分配与周转箱选择层次优化
A Hierarchical Optimization of Order Wave Assignment for Tote Selection in High-Density Case Storage Systems
李泰然 1苏志远1
作者信息
- 1. 北京邮电大学智能工程与自动化学院，北京 100876
- 折叠
摘要
针对现有方案中周转箱重复出库率高、系统负载波动大的突出问题，本文围绕高密度箱式库订单波次分配与周转箱选择的协同优化需求展开研究，提出一种层次化决策模型。该模型将优化问题拆解为两级决策：在系统层面，采用字典序多目标优化方法进行订单波次划分，以周转箱总出库量与单波次最大负载最小化为目标；在波次层面，基于既定订单集合约束开展独立选箱操作，以满足订单需求且降低周转箱出库距离为目标。据此，本文设计了大邻域搜索（LNS）启发式算法与贪心周转箱选择算法。通过不同订单规模、不同波次数组合的数值实验验证，结果表明所提方法在各类场景下均具备稳定的运行性能，可显著降低周转箱重复出库率并改善系统负载均衡性。本研究为高密度箱式库的上层波次规划，提供了兼具理论创新性与工程可实施性的决策支持方案。
Abstract
To address the prevalent issues of high tote repeated outbound rate and severe system load fluctuation in existing methods, this paper investigates the collaborative optimization of order wave allocation and tote selection for high-density case warehouses, proposing a hierarchical decision-making model. The model decomposes the problem into two levels: the system level conducts lexicographic multi-objective wave partitioning to minimize total outbound totes and maximum per-wave load; the wave level performs independent tote selection under fixed order sets to meet demands and minimize outbound distance. Correspondingly, a Large Neighborhood Search (LNS) heuristic and a greedy tote selection algorithm are designed. Numerical experiments across various order scales and wave quantities verify the method\'s stable performance, significantly reducing the repeated tote outbound rate and enhancing system load balancing. This study provides a theoretically innovative and engineering-feasible decision support scheme for upper-level wave planning in high-density case warehouses.关键词
物流工程/高密度箱式库/订单波次分配/周转箱选择/层级优化/大邻域搜索Key words
logistics engineering/high-density case storage systems/order wave assignment/tote selection/hierarchical optimization/large neighborhood search引用本文复制引用
李泰然,苏志远.高密度箱式库的订单波次分配与周转箱选择层次优化[EB/OL].(2026-03-23)[2026-03-24].http://www.paper.edu.cn/releasepaper/content/202603-215.学科分类
综合运输
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