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.
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G.C. Armour and E.S. Buffa, “A heuristic algorithm and simulation approach to relative location of facilities,” Management Science, vol. 9, pp. 294-309, 1963.
B. Bullnheimer, G. Kotsis, and C. Strauss, “Applying the ant system to the vehicle routing problem,” in Meta-heuristics: Advances and Trends in Local Search Paradigms for Optimization, S. Voss, S. Martello, I.H. Osman and C. Roucairol (Eds.), Kluwer: Boston, 1998, pp. 109-120.
M. Dorigo and G. Di Caro, “The ant colony optimization meta-heuristic,” in New Ideas in Optimization, D. Corne, M. Dorigo, and F. Glover (Eds.), McGraw-Hill, 1999, pp. 11-32.
M. Dorigo, G. Di Caro, and L.M. Gambardella, “Ant algorithms for discrete optimization,” Artificial Life, vol. 5, no. 2, pp. 137-172, 1999.
M. Dorigo and L.M. Gambardella, “Ant colony system: A cooperative learning approach to the travelling salesman problem,” IEEE Transactions on Evolutionary Computation, vol. 1, no. 1, pp. 53-66, 1997.
L.M. Gambardella, E.D. Taillard, and M. Dorigo, “Ant colonies for the quadratic assignment problem,” Journal of the Operational Research Society, vol. 50, no. 2, pp. 167-176, 1999.
M. Goetschalckx, “An interactive layout heuristic based on hexagonal adjacency graphs,” European Journal of Operational Research, vol. 63, pp. 304-321, 1992.
M. Gravel, W.L. Price, and C. Gagne, “Scheduling continuous casting of aluminum using a multiple objective ant colony optimization metaheuristic,” European Journal of Operational Research, vol. 143, no. 1, pp. 218-229, 2002.
S.S. Heragu and A. Kusiak, “Machine layout: An optimization and knowledge-based approach,” International Journal of Production Research, vol. 28, no. 4, pp. 615-635, 1990.
S. Sahni and T. Gonzalez, “P-complete approximation problem,” Journal of ACM, vol. 23, no. 3, pp. 555-565, 1976.
E.A. Silver and R. Peterson, Decision Systems for Inventory Management and Production Planning, 2nd edition, Wiley: New York, 1985.
A. Souilah, “Simulated annealing for manufacturing systems layout design,” European Journal of Operational Research, vol. 82, pp. 592-614, 1995.
T. Stutzle and H.H. Hoos, “Max-Min ant system,” Future Generation Computer Systems, vol. 16, pp. 889-914, 2000.
V. T'kindt, N. Monmarche, F. Tercinet, and D. Laugt, “An ant colony optimization algorithm to solve a 2-machine bicriteria flowshop scheduling problem,” European Journal of Operational Research, vol 142, no. 2, pp. 250-257, 2002.
J.A. Tompkins, J.A. White, Y.A. Bozer, E.H. Frazelle, J.M.A. Tanchoco, and J. Trevino, Facilities Planning, 2nd edition, Wiley: New York, 1996.
T. Yang and B.A. Peters, “Flexible machine layout design for dynamic and uncertain production environments,” European Journal of Operational Research, vol. 108, pp. 49-64, 1998.
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Corry, P., Kozan, E. Ant Colony Optimisation for Machine Layout Problems. Computational Optimization and Applications 28, 287–310 (2004). https://doi.org/10.1023/B:COAP.0000033965.99769.98
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DOI: https://doi.org/10.1023/B:COAP.0000033965.99769.98