Optimization of storage performance for generic tiered warehouse by Genetic Algorithm

A generic tiered warehouse (GTW) often features in adaptive layout and diversified efficiencies of transportation equipments or devices and so on. The storage optimization in GTW usually involves in storage allocation or assignment, transportation batching, routing and operational efficiency as well, which is comparably complicated more than in an automated storage and retrieval system (AS/RS). This paper considered GTW optimization problems of allocating the storages for inventory replenishment and order picking with known warehousing plan, and two optimization models were designed, respectively. The objective is to minimize the operational distance of warehousing equipments subject to the constraints of storage strategy, location loading capacity, carrying capacity of warehousing equipments, goods demands, etc. To solve the models, a dedicated Genetic Algorithm was designed, which embeds with heuristic algorithm. The problem solving consists of two structural phases: storage allocation or order picking with GA and transportation batching or routing solved with knapsack-based method, where heuristic and enumeration strategies are applied. The simulation experiments were implemented with the data in practical business and the results verified the effectiveness and efficiency of the proposed models and the designed algorithms.