Ant colony optimisation for milk-runs in manufacturing systems
by Yilmaz Uygun; Arenco Rustemaj
International Journal of Advanced Operations Management (IJAOM), Vol. 14, No. 2, 2022

Abstract: Milk-runs are route-based, cyclic material-handling systems with frequent and consistent yet need-based deliveries of standardised parts within lean manufacturing systems. While there are many solutions that are proposed to solve these kinds of optimisation problems, this paper seeks to bring the discussion to a more fundamental level. The research focuses on ant colony optimisation (ACO) which will be compared with the commonly used mixed integer programming (MIP). ACO outperforms MIP in all the instances that were used to benchmark both solutions. When presented with the capacitated vehicle routing problem (CVRP), chosen to represent the MR problem in routing and vehicle utilisation, our results show that ACO yields more optimal routes without sacrificing vehicle utilisation. The research highlights are mixed integer programming is the dominant method for milk-run-based vehicle routing problems, mixed integer programming and ant colony optimisation perform equally in terms of vehicle utilisation and ant colony optimisation yields more optimal routes without sacrificing vehicle utilisation.

Online publication date: Tue, 07-Jun-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Advanced Operations Management (IJAOM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com