A heuristic approach for the online order batching problem with multiple pickers

The Online Order Batching Problem with Multiple Pickers (OOBPMP) consists of optimizing the operations related to the picking process of orders in a warehouse, when the picking policy follows an order batching strategy. In this case, this variant of the well-known Order Batching Problem considers the existence of multiple workers in the warehouse and an online arrival of the orders. We study three different objective functions for the problem: minimizing the completion time, minimizing the picking time, and minimizing the differences in the workload among the pickers. We have identified and classified all previous works in the literature for the OOBPMP. Finally, we propose a multistart procedure hybridized with a Variable Neighborhood Descent metaheuristic to handle the problem. We test our proposal over well-known instances previously reported in the literature by empirically comparing the performance of our proposal with previous methods in the state of the art. The statistical tests corroborated the significance of the results obtained.

Automated summary

The study focuses on the Online Order Batching Problem with Multiple Pickers (OOBPMP) and proposes a multi-start procedure hybridized with a Variable Neighborhood Descent metaheuristic to solve the problem. Empirical comparisons on well-known instances from the literature show that the proposed method performs significantly better than previous methods.