Abstract
This paper analyzes the dynamics of a new selection scheme based on altruistic cooperation between individuals. The scheme, which we refer to as cooperative selection, extends from tournament selection and imposes a stringent restriction on the mating chances of an individual during its lifespan: winning a tournament entails a depreciation of its fitness value. We show that altruism minimizes the loss of genetic diversity while increasing the selection frequency of the fittest individuals. An additional contribution of this paper is the formulation of a new combinatorial problem for maximizing the similarity of proteins based on their secondary structure. We conduct experiments on this problem in order to validate cooperative selection. The new selection scheme outperforms tournament selection for any setting of the parameters and is the best trade-off, maximizing genetic diversity and minimizing computational efforts.
This is a preview of subscription content, log in via an institution to check access.
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
Alba, E., Dorronsoro, B.: The exploration/exploitation tradeoff in dynamic cellular genetic algorithms. IEEE Trans. Evolutionary Computation 9(2), 126–142 (2005)
Brünger, A.T., Adams, P.D., Clore, G.M., DeLano, W.L., Gros, P., Grosse-Kunstleve, R.W., Jiang, J., Kuszewski, J., Nilges, M., Pannu, N.S., Read, R.J., Rice, L.M., Simonson, T., Warren, G.L.: Crystallography and NMR System: A New Software Suite for Macromolecular Structure Determination. Acta Crystallographica Section D 54(5), 905–921 (1998)
Eiben, A.E., Schut, M.C., De Wilde, A.R.: Boosting genetic algorithms with self-adaptive selection. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1584–1589 (2006)
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer (2003)
Jin, Y., Branke, J.: Evolutionary optimization in uncertain environments-a survey. Trans. Evol. Comp. 9(3), 303–317 (2005)
Laredo, J.L.J., Dorronsoro, B., Fernandes, C., Merelo, J.J., Bouvry, P.: Oversized populations and cooperative selection: Dealing with massive resources in parallel infrastructures. In: Nicosia, G., Pardalos, P. (eds.) LION 7. LNCS, vol. 7997, pp. 444–449. Springer, Heidelberg (2013)
Laredo, J.L.J., Eiben, A.E., van Steen, M., Merelo, J.J.: On the run-time dynamics of a peer-to-peer evolutionary algorithm. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN X. LNCS, vol. 5199, pp. 236–245. Springer, Heidelberg (2008)
Miller, B.L., Goldberg, D.E.: Genetic algorithms, selection schemes, and the varying effects of noise. Evol. Comput. 4(2), 113–131 (1996)
Poli, R.: Tournament selection, iterated coupon-collection problem, and backward-chaining evolutionary algorithms. In: Wright, A.H., Vose, M.D., De Jong, K.A., Schmitt, L.M. (eds.) FOGA 2005. LNCS, vol. 3469, pp. 132–155. Springer, Heidelberg (2005)
Rost, B., Sander, C.: Combining evolutionary information and neural networks to predict protein secondary structure. Proteins 19(1), 55–72 (1994)
David Schaffer, J., Eshelman, L.J.: On crossover as an evolutionarily viable strategy. In: Belew, R.K., Booker, L.B. (eds.) ICGA, pp. 61–68. Morgan Kaufmann (1991)
Sokolov, A., Whitley, D.: Unbiased tournament selection. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, GECCO 2005, pp. 1131–1138. ACM, New York (2005)
Xie, H., Zhang, M.: Impacts of sampling strategies in tournament selection for genetic programming. Soft Comput. 16(4), 615–633 (2012)
Xie, H., Zhang, M., Andreae, P.: Another investigation on tournament selection: modelling and visualisation. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, GECCO 2007, pp. 1468–1475. ACM, New York (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jiménez Laredo, J.L., Nielsen, S.S., Danoy, G., Bouvry, P., Fernandes, C.M. (2014). Cooperative Selection: Improving Tournament Selection via Altruism. In: Blum, C., Ochoa, G. (eds) Evolutionary Computation in Combinatorial Optimisation. EvoCOP 2014. Lecture Notes in Computer Science, vol 8600. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44320-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-662-44320-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-44319-4
Online ISBN: 978-3-662-44320-0
eBook Packages: Computer ScienceComputer Science (R0)