Abstract
This paper introduces a new algorithm to deal with multi-objective combinatorial and continuous problems. The algorithm is an extension of a previous one designed to deal with single objective combinatorial problems. The original purpose of the single objective version was to study in a rigorous way the properties the search graph of a particular problem needs to hold so that a randomized local search heuristic can find the optimum with high probability. The extension of these results to better understand multi-objective combinatorial problems seems to be a promising line of research. The work presented here is a first small step in this direction. A detailed description of the multi-objective version is presented along with preliminary experimental results on a well known combinatorial problem. The results show that the algorithm has the desired characteristics.
This is a preview of subscription content, log in via an institution to check access.
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)
Aldous, D., Vazirani, U.: Go with the winners algorithms. In: Proceedings of the 35th IEEE Symposium on Foundations of Computer Science, pp. 492–501 (1994)
Carson, T.: Empirical and analitic approaches to understanding local search heuristics. PhD Thesis, University of California. San Diego, California (2001)
Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting algorithm for multi-objective optimization: NSGA-II. In: Deb, K., Rudolph, G., Lutton, E., Merelo, J.J., Schoenauer, M., Schwefel, H.-P., Yao, X., et al. (eds.) PPSN 2000. LNCS, vol. 1917, pp. 849–858. Springer, Heidelberg (2000)
Dimitriou, A., Impagliazzo, R.: Towards a rigorous analysis of local optimization algorithms. In: Proceedings of the 25th ACM Symposium on the Theory of Computing (1996)
Dimitriou, A., Impagliazzo, R.: Go-with-the-winner algorithms for graph bisection. In: Proceedings of the 9th Annual SIAM Symposium on Discrete Algorithms, pp. 510–520 (1998)
Brizuela, C.A., Aceves, R.: Experimental genetic operators analysis for the multi-objective permutation flowshop. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 578–592. Springer, Heidelberg (2003)
Aceves, R., Brizuela, C.A.: Análisis Experimental de Operadores Genéticos en NSGA-II para un Problema de Calendarización Multi-objetivo. In: Botello, S., Hernández, A., Coello, C. (eds.) Congreso Mexicano de Computación Evolutiva, pp. 55–66 (2003)
Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, Chichester (2001)
Isibuchi, H., Murata, T.: Multi-objective Genetic Local Search Algorithm. In: Proceedings of the 1996 International Conference on Evolutionary Computation, pp. 119–124 (1996)
Tamaki, H., Nishino, E.: Genetic Algorithm approach to multi-objective scheduling problems with regular and non-regular objective functions. In: Proceedings of IFAC LSS 1998, pp. 289–294 (1998)
Bagchi, T.P.: Multiobjective Scheduling by Genetic Algorithms. Kluwer Academic Publishers, Dordrecht (1999)
Srinivas, N., Deb, K.: Multi-Objective function optimization using non-dominated sorting genetic algorithms. Evolutionary Computation 2(3), 221–248 (1995)
Serafini, P.: Simulated Annealing for Multiple Objective Optimization Problems. In: Tzeng, G., Wang, H., Wen, U., Yu, P. (eds.) Proceedings of the Tenth International Conference on Multiple Criteria Decision Making: Expand and Enrich the Domains of Thinking and Application, vol. 1, pp. 283–292 (1994)
Thompson, M.: Application of Multi Objective Evolutionary Algorithms to Analogue Filter Tuning. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D. (eds.) EMO 2001. LNCS, vol. 1993, pp. 546–559. Springer, Heidelberg (2001)
Mariano, C.E., Morales, E.: MOAQ an Ant-Q Algorithm for Multiple Objective Optimization Problems. In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honavar, V., Jakiela, M., Smith, R.E. (eds.) Genetic and Evolutionary Computing COnference (GECCO 1999), vol. 1, pp. 894–901 (1999)
Gambardella, L.M., Taillard, E., Agazzi, G.: MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. In: Corne, D., Dorigo, M., Glover, F. (eds.) New Ideas in Optimization, pp. 63–76. McGraw Hill, New York (1999)
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)
Hansen, M.P.: Tabu Search in Multiobjective Optimisation: MOTS. In: Proceedings of the 13th International Conference on Multiple Criteria Decision Making, MCDM1997 (1997)
Gandibleux, X., Mezdaoui, N., Fréville, A.: A Tabu Search Procedure to Solve Combinatorial Optimisation Problems. In: Caballero, R., Ruiz, F., Steuer, R.E. (eds.) A Collection of Test Problems for Constrained Global Optimization Algorithms. Lecture Notes in Economics and Mathematical Systems, vol. 455, pp. 291–300. Springer, Heidelberg (1997)
Binh, T.T., Korn, U.: An evolution strategy for the multiobjective optimization. In: The Second International Conference on Genetic Algorithms (Mendel 1996), pp. 23–28 (1996)
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
Brizuela, C.A., Gutiérrez, E. (2005). Multi-objective Go with the Winners Algorithm: A Preliminary Study. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_15
Download citation
DOI: https://doi.org/10.1007/978-3-540-31880-4_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24983-2
Online ISBN: 978-3-540-31880-4
eBook Packages: Computer ScienceComputer Science (R0)