Research on order batching optimization based on improved NSGA-II algorithm - Huiyue Xu; Juping Shao; Yanan Sun (PLoS ONE, 2025)
In the context of e-commerce, the order batching optimization problem in e-commerce warehousing centers has been addressed by establishing a model aimed at minimizing the order picking time, order delay costs, and picking costs, as well as achieving workload balance. An improved NSGA-II algorithm has been designed, which enhances the search capability and solution diversity by introducing new selection mechanisms and crossover mutation strategies. This approach more effectively balances multiple optimization objectives and validates the effectiveness of the model and algorithm with case studies, while also conducting sensitivity analysis on model parameters. The research results indicate that the established model and the designed algorithm are effective, providing a theoretical basis and practical significance for the optimization of order picking efficiency in e-commerce distribution centers.