Performance comparison of meta-heuristics for the multiblock warehouse order picking problem

Abstract

This study focuses on streamlining the order-picking process in a warehouse. We consider determining the picking sequence of items in a pick-list to minimize the total traveled distance in a multiblock warehouse where a low-level picker-to-parts manual picking system is employed. We assume that the items are stored randomly in the warehouse. First we construct a distance matrix of the shortest path between any pair of items. Next using the distance matrix we implement two meta-heuristics-the tabu search algorithm and the iterated greedy algorithm-to determine the picking sequence with the minimum total traveled distance. Through a numerical study the performances of the meta-heuristic algorithms are compared with those of popular rule-based heuristics (S-shape largest gap and Combined+) and the best-known solutions. We conducted the numerical study in two stages. In the first stage we considered a two-block rectangular warehouse and in the second stage we considered a three-block rectangular warehouse. The performance of the heuristics was calculated based on the optimal solution when available or the best calculated bound when the optimal solution is not available. We observed that the iterated greedy algorithm significantly outperforms the other heuristics for both stages. © 2022 Elsevier B.V. All rights reserved.