Order Batches Approaches in Warehouses with Low-Level Picker-to-Parts Systems: A Practical Perspective on Picking Optimization Methods

The increasing requirements imposed by the dynamics of world consumer markets have intensified the competitiveness between companies throughout the Global Supply Chain. One of the main challenges of Supply Chain Management to deal with customer impositions is finding ways to optimize the order picking systems inside Warehouses (WAs). Most picking systems in the world are still manual and consist of a protracted activity which causes more impact on the costs of a WA. Therefore, optimizing this system type is the main objective towards efficiency and competitiveness of these WAs. The most expensive and common manual picking system is the low-level picker-to-parts, which is characterized as an optimization problem whose nature is NP-hard. An important strategy for optimizing manual picking in low-level picker-to-parts systems is the Order Batching Problem (OBP). In OBP, orders or products are clumped in batches according to predefined criteria so as to reduce the picking time and total cost. Despite the efficiency of the OBP, there are still many gaps related to the low-level picker-to-parts reality which require better Picking Optimization Methods (POMs). A fundamental issue for the POMs is the trade-off between the urgency of satisfying the order fulfillment timelines and the efficiency of the picking processes required of WAs . In this sense, a series of POMs pertinent to different contexts and solution approaches have been proposed to the OBP. This chapter aims to provide a practical perspective on POMs proposed to the OBP in WAs with low-level picker-to-parts systems and order due dates or Stock Keeping Units. We present a review of the state-of-the-art focusing on the main dilemmas around the levels of adaptation and quality of the proposed solutions by POMs. The theoretical framework and basic mathematical modeling are reviewed with special attention to the personalization of a solution design more advanced to the POMs. Furthermore, a brief inference about the main gaps concerning the studied subject is presented in order to provide insights for better handling of the new challenges related to the OBP. This theoretical foundation brings important contributions and the basic guidelines for studies aimed at formulating of more suitable, flexible, and multi-objective POMs. Hence, this chapter might support managers, students, and researchers through a series of key questions inherent to the picking optimization processes and decision making in WAs.