Improving order-picking performance by optimizing order batching in multiple-cross-aisle warehouse systems: A case study from e-commerce in China

摘要

This article explores the order batching problem (OBP), in warehouse of e-commerce companies. Based on the real E-commence warehouse case, we present a valid tabu search(TS) algorithm to determine how to group the orders in batches, with a greed-based seed heuristic method generating its initial solution. In tabu search, a modified combined picker routing algorithm for the multiple-cross-aisle picker routing problem is embedded in it to calculate the value of fitness function and evaluate the performance of the tabu algorithm. These algorithms are experimentally tested on real warehouse operational data cases from a B2C company warehouse. Comparing with the current applied operational patterns, our proposed methods are able to improve the order-picking efficiency greatly.