基于改进自适应大邻域搜索算法的电商仓库布局优化研究

Research on E-Commerce Warehouse Layout Optimization Based on an Improved Adaptive Large Neighborhood Search Algorithm

摘要: 随着电子商务行业快速发展和网络零售规模持续扩大，电商仓库订单规模不断增加，仓储作业效率和空间利用水平面临更高要求。在实际仓库改造过程中，部分功能区受到设备安装、设施配置和业务需求等因素影响，存在不可移动或调整受限的问题，使传统仓库布局优化方法难以直接适用。针对部分功能区固定约束下的仓库布局优化问题，本文以搬运成本最小化为单一目标，并将物流量与距离的乘积作为结果分析指标，构建考虑边界约束、不重叠约束、功能区间距约束以及固定功能区坐标约束的仓库布局优化模型，并设计改进自适应大邻域搜索算法进行求解。算法采用双层编码方式表示可调整功能区排序关系和横向间距，通过设计多种破坏算子与修复算子实现布局方案搜索，并结合分段自适应权重、模拟退火接受准则、动态破坏规模调整和停滞升温机制提升算法的全局搜索能力和收敛性能。以某电商仓库为算例进行验证，结果表明，改进算法能够在保持1、8、10和14号功能区位置固定的条件下，对其余功能区进行合理调整优化。优化后仓库总物流强度由12,080,300 kg·m/周降低至9,920,500 kg·m/周，减少2,159,800 kg·m/周，降幅达到17.88%；周搬运成本由5167.68元降低至4243.77元，同样降低17.88%。研究结果表明，所构建模型能够有效解决部分功能区不可移动约束下的仓库布局优化问题，在满足实际改造条件的基础上降低物流搬运成本，提高仓储运行效率，为电商企业仓库布局调整与优化提供理论依据和决策参考。

Abstract: With the rapid development of the e-commerce industry and the continuous expansion of online retail, the order volume of e-commerce warehouses is constantly increasing, and higher requirements are being placed on warehousing operation efficiency and space utilization. In the actual warehouse renovation process, some functional areas are affected by factors such as equipment installation, facility configuration, and business needs, resulting in some functional areas being immovable or subject to limited adjustment, making traditional warehouse layout optimization methods difficult to apply directly. This paper addresses the warehouse layout optimization problem under the constraint that some functional areas are fixed. With handling cost minimization as the single objective and the flow-distance product as a performance indicator, a warehouse layout optimization model considering boundary constraints, non-overlapping constraints, functional area spacing constraints, and fixed functional area coordinate constraints is constructed. An improved adaptive large neighborhood search algorithm is designed to solve the problem. The algorithm uses a two-layer encoding method to represent the adjustable functional area ordering relationship and lateral spacing. Various destruction and repair operators are designed to search for layout schemes. Furthermore, piecewise adaptive weights, simulated annealing acceptance criteria, dynamic destruction scale adjustment, and stagnation warming mechanism are combined to improve the algorithm’s global search capability and convergence performance. A case study of an e-commerce warehouse is used for verification. The results show that the improved algorithm can reasonably adjust and optimize the remaining functional areas while keeping the positions of functional areas 1, 8, 10, and 14 fixed. After optimization, the total logistics intensity of the warehouse decreased from 12,080,300 kg·m/week to 9,920,500 kg·m/week, a reduction of 2,159,800 kg·m/week, representing a decrease of 17.88%. Weekly handling costs also decreased from RMB 5167.68 to RMB 4243.77, a reduction of 17.88%. The research results indicate that the constructed model can effectively solve the warehouse layout optimization problem under the constraint that some functional areas are immovable. It reduces logistics handling costs and improves warehousing efficiency while meeting actual renovation conditions, providing a theoretical basis and decision-making reference for warehouse layout adjustment and optimization in e-commerce enterprises.