A classification approach to order picking systems and policies: Integrating automation and optimization for future research

Abstract

Picking system optimization is the main condition for improving customer satisfaction and warehouse efficiency. However, related literature does not present a standard classification for the different picking systems and warehouses. This issue implies a lack of scientific uniformity and the difficulty of conducting comparative studies on which the best approaches are, applied to picking problems and/or warehouses. Therefore, this paper aims to provide a theoretical framework on the picking system classifications most used by researchers. The research is descriptive in nature and focuses on the two major categories of picking systems: i) according to automation strategies and processes; ii) according to picking optimization policies and methods. These classifications have been revised so that researchers can combine them with a wide range of picking systems and warehouses. The main contribution of this paper is to provide a better understanding of the main specificities regarding classifications inherent to picking systems and warehouses. We also demonstrate that approaches integrating people, warehouses, technological advances, and adaptation of multi- objective algorithms should be the focus of researchers. The theoretical framework presented corroborates with future studies aimed at managing and adapting picking systems and warehouses. We concluded that integrating picking strategies and policies is critical to dealing with technological advances in warehouses.