Order picking and storage optimisation in a warehouse using agent-based modelling

P. Raghuram, S. Anuj Jain and Souryadeep Mazumder

International Journal of Operational Research, 2023, vol. 48, issue 1, 47-62

Abstract: Warehouse management is an integral part of the supply chain and optimisation of warehouse operations can minimise redundant movements of pickers and can reduce processing time, thereby maximising the profits. In this paper, our objective is to develop a simulation model to find the optimal number of forklifts and arrival rate of goods by considering various factors like distance travelled by pickers, picker utilisation, storage and retrieval times. The warehouse layout is found through the number of racks, number of vertical levels and aisle width using genetic algorithm in MATLAB. The objective function is to minimise the total operational costs considering space and arrival constraints. The warehouse design parameters after optimisation are used in the simulation model to develop a new layout. The number of pickers and arrival rate of goods is obtained, analysed and compared. It is observed that further reduction in the aforementioned factors are obtained.

Keywords: warehouse optimisation; order picking; storage; handling; agent-based modelling; genetic algorithms. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=133745 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:48:y:2023:i:1:p:47-62

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().