Ant Colony Optimisation for Machine Layout Problems

Authors:
Paul Corry;Erhan Kozan
Affiliations:
School of Mathematical Sciences, Queensland University of Technology, Australia;School of Mathematical Sciences, Queensland University of Technology, Australia. e.kozan@qut.edu.au
Venue:
Computational Optimization and Applications
Year:
2004

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Abstract

Flexible machine layout problems describe the dynamic arrangement of machines to optimise the trade-off between material handling and rearrangement costs under changing and uncertain production environments. A previous study used integer-programming techniques to solve heuristically reduced versions of the problem. As an alternative, this paper introduces an ant colony optimisation (ACO) algorithm to generate good solutions. Experimental results are presented, with ACO obtaining better solutions than the reduction heuristic.