| dc.description.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. | en_US |
