An effective batching method based on the artificial bee colony algorithm for order picking

Abstract

Order picking costs most of operating expenses in the warehouse management. Generally, order batching is effective in reducing the total travel distance of order picking. However, how to realize order batching is an NP-hard problem. It is difficult to find the optimal solution of order batching in polynomial time. Some deterministic methods are applied to small-scale order batching problems; while some heuristic algorithms are potential for large-scale order batching problems. Inspired by the behaviors of honey bee swarms, artificial bee colony (ABC) algorithms have been developed as potential computational approaches and performed well in scientific researches and engineering applications. To minimize the total travel distance of order picking, this paper proposes an effective batching method based on an artificial bee colony algorithm (ABC-BM). A series of numerical simulation experiments about order batching are arranged. Compared to GA-BM, the proposed ABC-BM algorithm is more efficient in optimizing different-scale order picking problems.