Azadnia, Amir Hossein and Taheri, Shahrooz and Ghadimi, Pezhman and Mat Saman, Muhamad Zameri and Wong, Kuan Yew (2013) Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms. The Scientific World Journal, 2013 (246578). pp. 1-13. ISSN 2356-6140

Preview

Download (976kB) | Preview

Abstract

One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

Item Type:	Article
Keywords:	Order Batching; Warehouses; Minimizing; Total; Tardiness; Hybrid Approach; Weighted Association; Rule; Mining; Genetic Algorithms;
Academic Unit:	Faculty of Social Sciences > School of Business
Item ID:	15909
Identification Number:	https://doi.org/10.1155/2013/246578
Depositing User:	Amir Azadnia
Date Deposited:	03 May 2022 15:04
Journal or Publication Title:	The Scientific World Journal
Publisher:	Hindawi
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads