A storage assignment heuristic method based on genetic algorithm for a pick-and-pass warehousing system

• A heuristic storage assignment policy is developed based on genetic algorithm for a picker-and-pass system.
• The balance of the workloads among all pickers has a great impact on the efficiency of the picker-and-pass system.
• A picker is unproductive while he/she calls for an emergency replenishment that impacts supply chain performance.
• The proposed heuristic policy improves the order picking efficiency in a picker-and-pass system.

An order storage assignment problem (SAP) is to find an effective way to locate products in a warehouse in order to improve the operational efficiency of order picking. Since SAP is an NP-hard problem, many heuristic algorithms have been proposed. Most of previous researches focused on picker-to-parts warehousing systems or automated storage and retrieval systems. However, pick-and-pass systems play an important role for the faster delivery of small and frequent orders of inventory with the rise of e-commerce and e-business in the global supply chain. Two factors lead to idle time of pickers in a pick-and-pass system: picking line imbalance and shortage replenishment of products. This paper develops a genetic based heuristic method to solve SAP for a pick-and-pass system with multiple pickers to determine the appropriate storage space for each product and balance the workload of each picking zone so that the performance of the system can be improved. A simulation model based on FlexSim is used to implement the proposed heuristic algorithm and compare the throughput for different storage assignment methods as well. The results indicate that the proposed heuristic policy outperforms existing assignment methods in a pick-and-pass system.