Two-Stage Metaheuristic Algorithms for Order-Batching and Routing Problems

Abstract

Because of time and cost constraints, item picking plays a major role in warehouse operations. Considering diversified orders and a constant warehouse design, deciding how to combine each batch and picker route effectively is a challenge in warehouse management. In this study, we focus on the evaluation of order-batching strategies for a single picker facing multiple orders with the objective of minimizing the total traveling distance. We propose two-stage simulated annealing and variable neighborhood search algorithms to solve the combined problem. The orders are first merged into batches, followed by determining the sequence in each batch. The computational analysis revealed that the best-fit-decreasing (BFD) batch ordering strategy in the two-stage algorithms, the variable neighborhood search algorithm, obtained superior solutions to those of the simulated annealing algorithm.