Optimizing Storage and Picking Routes in Dual-Zone Warehouses Using Genetic Algorithms: A Case Study of YY Company

Abstract

This research addresses the optimization of storage locations and picking routes in YY’s dual-zone warehouse, with the goal of cutting warehousing costs and enhancing operational efficiency. As the economy shifts and industrial structures upgrade, the logistics industry’s significance in the national economy grows increasingly evident. The Apriori algorithm discerns order item associations, informing the reorganization of storage allocations for optimized efficiency. On this basis, a target optimization model is constructed to further enhance the rationality of the storage layout. Regarding the optimization of picking paths, this paper presents a path optimization model tailored for multi-vehicle operations, based on the layout characteristics of YY’s warehouse. This paper validates the improved genetic algorithm’s effectiveness and practicality in optimizing double-zone warehouse storage and picking paths through Matlab simulations and comparisons with traditional methods.