Distribution Tree-Building Real-Valued Evolutionary Algorithm
This article describes a new model of probability density function and its use in estimation of distribution algorithms. The new model, the distribution tree, has interesting properties and can form a solid basis for further improvements which will make it even more competitive. Several comparative experiments on continuous real-valued optimization problems were carried out and the results are promising. It outperformed the genetic algorithm using the traditional crossover operator several times, in the majority of the remaining experiments it was comparable to the genetic algorithm performance.
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- 1.Bosman, P.A.N., Thierens, D.: Continuous iterated density estimation evolutionary algorithms within the IDEA framework. In: Workshop Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2000), pp. 197–200 (2000)Google Scholar
- 3.Gallagher, M.R., Frean, M., Downs, T.: Real-valued evolutionary optimization using a flexible probability density estimator. In: Genetic and Evolutionary Computation Conference (GECCO 1999)Google Scholar
- 5.Očenášek, J., Schwarz, J.: Estimation of Distribution Algorithm for Mixed Continuous-Discrete Optimization Problems. In: 2nd Euro-International Symposium on Computational Intelligence, pp. 227–232. IOS Press, Kosice (2002) ISBN 3-540-444139-5, ISSN 0302-9743Google Scholar
- 6.Pelikan, M., Goldberg, D.E., Lobo, F.: A survey of optimization by building and using probabilistic models. Technical Report IlliGAL Report No. 98018, University of Illinois, Urbana-Champaign (September 1999)Google Scholar
- 7.Pošík, P.: Comparing various marginal probability models in evolutionary algorithms. In: Ošmera, P. (ed.) MENDEL 2003, Brno, vol. 1, pp. 59–64. Brno University (2003) ISBN 80-214-2411-7Google Scholar
- 8.Tsutsui, S., Pelikan, M., Goldberg, D.E.: Evolutionary algorithm using marginal histogram models in continuous domain. Technical Report IlliGAL Report No. 2001019, University of Illinois, Urbana-Champaign (March 2001)Google Scholar