Title: Ant colony optimisation for milk-runs in manufacturing systems

Authors: Yilmaz Uygun; Arenco Rustemaj

Addresses: Logistics Engineering and Technologies Group, Department of Mathematics and Logistics, Jacobs University, Campus Ring 1, 28759 Bremen, Germany ' Logistics Engineering and Technologies Group, Department of Mathematics and Logistics, Jacobs University, Campus Ring 1, 28759 Bremen, Germany

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.

Keywords: ant colony optimisation; ACO; mixed integer programming; MIP; milk-run; capacitated vehicle routing problem; CVRP; lean manufacturing.

DOI: 10.1504/IJAOM.2022.123267

International Journal of Advanced Operations Management, 2022 Vol.14 No.2, pp.167 - 181

Accepted: 28 Jun 2021
Published online: 07 Jun 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article