International Journal of Industrial Engineering and Management

Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut ero labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco.

GUIDE FOR AUTHORS SUBMIT MANUSCRIPT
Vol. 15 No. 2 (2024)
Original Research Article

An efficient correlation-based storage location assignment heuristic for multi-block multi-aisle warehouses

Md. Saiful Islam
Khulna University of Engineering & Technology, Industrial Engineering and Management, Khulna, Bangladesh
Md. Kutub Uddin
Khulna University of Engineering & Technology, Mechanical Engineering, Khulna, Bangladesh

Published 2024-06-11

abstract views: 70 // FULL TEXT ARTICLE (PDF): 8


Keywords

  • Order picking,
  • Storage location assignment,
  • Correlated storage,
  • Warehouse,
  • Simulation

How to Cite

Islam, M. S., & Uddin, M. K. (2024). An efficient correlation-based storage location assignment heuristic for multi-block multi-aisle warehouses. International Journal of Industrial Engineering and Management, 15(2), 125–139. https://doi.org/10.24867/IJIEM-2024-2-352

Abstract

The most labor-intensive and time-consuming part of warehouse operations is order picking. This paper proposes a correlation-based storage location assignment (CBSLA) approach to minimize the travel distance of the picker in a picker-to-parts warehouse. At first, the proposed CBSLA approach forms some groups of stock-keeping units (SKUs) for different warehouse aisles. Then these groups of SKUs are assigned to the storage locations considering both the correlations between SKUs in a group and the correlation between groups of SKUs for efficient order picking. The effectiveness of the proposed method is measured for various warehouse configurations using simulation and compared with other well-known storage allocation methods.

Article history: Received (May 6, 2023); Revised (March 21, 2024); Accepted (April 6, 2024); Published online (April 16,2024)

PlumX Metrics

Dimensions Citation Metrics