Abstract
Few applications of ACO algorithms to multiobjective problems have been presented so far and it is not clear how to design an effective ACO algorithms for such problems. In this article, we study the performance of several ACO variants for the biobjective Quadratic Assignment Problem that are based on two fundamentally different search strategies. The first strategy is based on dominance criteria, while the second one exploits different scalarizations of the objective function vector. Further variants differ in the use of multiple colonies, the use of local search, and the pheromone update strategy. The experimental results indicate that the use of local search procedures and the correlation between objectives play an essential role in the performance of the variants studied in this paper.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Burkard, R.E., C¸ela, E., Pardalos, P.M., Pitsoulis, L.S.: The quadratic assignment problem. In: Pardalos, P.M., Du, D.-Z. (eds.) Handbook of Combinatorial Optimization, pp. 241–338. Kluwer Academic Publishers, Dordrecht (1998)
Cȩla, E.: The Quadratic Assignment Problem: Theory and Algorithms. Kluwer Academic Publishers, Dordrecht (1998)
Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential performance assessment of stochastic optimisers and the attainment function. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D.W. (eds.) EMO 2001. LNCS, vol. 1993, pp. 213–225. Springer, Heidelberg (2001)
Dean, A., Voss, D.: Design and Analysis of Experiments. Springer, Heidelberg (1999)
Doerner, K., Hartl, R.F., Reimann, M.: Cooperative ant colonies for optimizing resource allocation in transportation. In: Boers, E.J.W., Gottlieb, J., Lanzi, P.L., Smith, R.E., Cagnoni, S., Hart, E., Raidl, G.R., Tijink, H. (eds.) EvoIASP 2001, EvoWorkshops 2001, EvoFlight 2001, EvoSTIM 2001, EvoCOP 2001, and EvoLearn 2001. LNCS, vol. 2037, pp. 70–79. Springer, Heidelberg (2001)
Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)
Gilmore, P.C.: Optimal and suboptimal algorithms for the quadratic assignment problem. Journal of the SIAM 10, 305–313 (1962)
Guntsch, M.G., Middendorf, M.: Solving multi-criteria optimization problems with population-based ACO. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 464–478. Springer, Heidelberg (2003)
Hamacher, H., Nickel, S., Tenfelde-Podehl, D.: Facilities layout for social institutions. In: Operation Research Proceedings 2001, pp. 229–236. Springer, Heidelberg (2001)
Iredi, S., Merkle, D., Middendorf, M.: Bi-criterion optimization with multi colony ant algorithms. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D.W. (eds.) EMO 2001. LNCS, vol. 1993, pp. 359–372. Springer, Heidelberg (2001)
Knowles, J., Corne, D.: Towards landscape analysis to inform the design of hybrid local search for the multiobjective quadratic assignment problem. In: Abraham, A., et al. (eds.) Soft Computing Systems: Design, Management and Applications, pp. 271–279. IOS Press, Amsterdam (2002)
Knowles, J.D., Corne, D.W.: Instance generators and test suites for the multiobjective quadratic assignment problem. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 295–310. Springer, Heidelberg (2003)
Paquete, L., Chiarandini, M., Stützle, T.: Pareto local optimum sets in the biobjective traveling salesman problem: An experimental study. In: Gandibleux, X., et al. (eds.) Metaheuristics for Multiobjective Optimisation. LNEMS 535, Springer, Heidelberg (2004)
Paquete, L., Stützle, T.: A study of local search algorithms for the biobjective QAP with correlated flow matrices. European Journal of Operational Research (2004) (to appear)
Sahni, S., Gonzalez, T.: P-complete approximation problems. Journal of the ACM 23, 555–565 (1976)
Stützle, T., Hoos, H.H.: MAX-MIN Ant System. Future Generation Computer Systems 16, 889–914 (2000)
Taillard, É.D.: A comparison of iterative searches for the quadratic assignment problem. Location Science 3, 87–105 (1995)
Taillard, É.D.: Robust Taboo Search for the Quadratic Assingnment Problem. Parallel Computing 17, 443–455 (1991)
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Grunert da Fonseca, V.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Transactions on Evolutionary Computation 7, 117–132 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
López-Ibáñez, M., Paquete, L., Stützle, T. (2004). On the Design of ACO for the Biobjective Quadratic Assignment Problem. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2004. Lecture Notes in Computer Science, vol 3172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28646-2_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-28646-2_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22672-7
Online ISBN: 978-3-540-28646-2
eBook Packages: Springer Book Archive