A Comparative Study Between Two Solving Scenarios For The Order Batching And Picking Route Problem - A Case Of The Automotive Aftermarket Industry

Abstract

Order Picking is a fundamental operational task at fulfillment facilities. Four sub problems have been identified within the Order Picking process: Order Batching, Batch Assignment, Batch Sequencing, and Picker Routing. In particular, the Order Batching sub-problem groups customer orders into batches to make picking easier for pickers while the Picker Routing sub-problem aims to minimize the length of distance that pickers must complete when picking a batch. This article, which was inspired by and involves optimization for an automotive aftermarket company, focuses on the integration of order batching and picking route decisions considering in mind the objective of minimizing the total travel distance to collect all orders while also taking the picking device's capacity into account. To be more specific, we proposed a work of Geospatial Clustering (GC) for Order Batching Problem (OBP) and Genetic Algorithm (GA) for Picking Route Problem (PRP). This paper also offers a thorough description of the modeling process along with a numerical example for more clarification. A Single Order picking approach - the strategy of current case study is employed to evaluate the algorithm's performance.