Abstract
We propose a new version of a multiobjective coevolutionary algorithm. The main idea of the proposed approach is to concentrate the search effort on promising regions that arise during the evolutionary process as a product of a clustering mechanism applied on the set of decision variables corresponding to the known Pareto front. The proposed approach is validated using several test functions taken from the specialized literature and it is compared with respect to its previous version and another approach that is representative of the state-of-the-art in evolutionary multiobjective optimization.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Coello Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, New York (2002)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA–II. IEEE Transactions on Evolutionary Computation 6, 182–197 (2002)
Knowles, J.D., Corne, D.W.: Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy. Evolutionary Computation 8, 149–172 (2000)
Coello Coello, C.A., Reyes Sierra, M.: A Coevolutionary Multi-Objective Evolutionary Algorithm. In: Proceedings of 2003 CEC, vol. 1, pp. 482–489. IEEE Press, Los Alamitos (2003)
Paredis, J.: Coevolutionary algorithms. In: Bäck, T., Fogel, D.B., Michalewicz, Z. (eds.) The Handbook of Evolutionary Computation, 1st supplement, pp. 225–238. Institute of Physics Publishing and Oxford University Press, Oxford (1998)
Potter, M., Jong., K.D.: A cooperative coevolutionary approach to function optimization. In: Proceedings from PPSN V, pp. 530–539. Springer, Heidelberg (1994)
Parmee, I.C., Watson, A.H.: Preliminary Airframe Design Using Co-Evolutionary Multiobjective Genetic Algorithms. In: Proceedings of GECCO 1999, vol. 2, pp. 1657–1665. Morgan Kaufmann, San Francisco (1999)
Keerativuttitumrong, N., Chaiyaratana, N., Varavithya, V.: Multi-objective Co-operative Co-evolutionary Genetic Algorithm. In: Guervós, J.J.M., Adamidis, P.A., Beyer, H.-G., Fernández-Villacañas, J.-L., Schwefel, H.-P. (eds.) PPSN 2002. LNCS, vol. 2439, pp. 288–297. Springer, Heidelberg (2002)
Tan, K., Chew, Y., Lee, T., Yang, Y.: A cooperative coevolutionary algorithm for multiobjective optimization. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp. 390–395. IEEE Press, Los Alamitos (2003)
Iorio, A., Li, X.: A cooperative coevolutionary multiobjective algorithm using non-dominated sorting. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 537–548. Springer, Heidelberg (2004)
Fonseca, C.M., Fleming, P.J.: Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of the Fifth International Conference on Genetic Algorithms, pp. 416–423. Morgan Kauffman Publishers, San Francisco (1993)
Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice Hall, New Jersey (1988)
Van Veldhuizen, D.A.: Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. PhD thesis, Department of Electrical and Computer Engineering. Air Force Institute of Technology, Wright-Patterson AFB, Ohio (1999)
Van Veldhuizen, D.A., Lamont, G.B.: On Measuring Multiobjective Evolutionary Algorithm Performance. In: 2000 CEC, vol. 1, pp. 204–211. IEEE Service Center, Los Alamitos (2000)
Schott, J.R.: Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization. Master’s thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts (1995)
Zitzler, E., Deb, K., Thiele, L.: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Evolutionary Computation 8, 173–195 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sierra, M.R., Coello, C.A.C. (2005). Coevolutionary Multi-objective Optimization Using Clustering Techniques. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_61
Download citation
DOI: https://doi.org/10.1007/11579427_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
Online ISBN: 978-3-540-31653-4
eBook Packages: Computer ScienceComputer Science (R0)