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Article

Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA

Authors:

Peter A. N. Bosman,

Dirk ThierensAuthors Info & Claims

PPSN VI: Proceedings of the 6th International Conference on Parallel Problem Solving from Nature

Pages 767 - 776

Published: 18 September 2000 Publication History

Abstract

The direct application of statistics to stochastic optimization based on iterated density estimation has become more important and present in evolutionary computation over the last few years. The estimation of densities over selected samples and the sampling from the resulting distributions, is a combination of the recombination and mutation steps used in evolutionary algorithms. We introduce the framework named IDEA to formalize this notion. By combining continuous probability theory with techniques from existing algorithms, this framework allows us to define new continuous evolutionary optimization algorithms.

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Cited By

Dong WWang YZhou M(2019)A latent space-based estimation of distribution algorithm for large-scale global optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3390-823:13(4593-4615)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s00500-018-3390-8
Liagkouras KMetaxiotis K(2017)An experimental analysis of a new two-stage crossover operator for multiobjective optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1810-621:3(721-751)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s00500-015-1810-6
Karshenas HSantana RBielza CLarrañAga P(2013)Regularized continuous estimation of distribution algorithmsApplied Soft Computing10.1016/j.asoc.2012.11.04913:5(2412-2432)Online publication date: 1-May-2013
https://dl.acm.org/doi/10.1016/j.asoc.2012.11.049
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Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA

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Published In

cover image Guide Proceedings

PPSN VI: Proceedings of the 6th International Conference on Parallel Problem Solving from Nature

September 2000

881 pages

ISBN:3540410562

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 18 September 2000

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Cited By

Dong WWang YZhou M(2019)A latent space-based estimation of distribution algorithm for large-scale global optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3390-823:13(4593-4615)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s00500-018-3390-8
Liagkouras KMetaxiotis K(2017)An experimental analysis of a new two-stage crossover operator for multiobjective optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1810-621:3(721-751)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s00500-015-1810-6
Karshenas HSantana RBielza CLarrañAga P(2013)Regularized continuous estimation of distribution algorithmsApplied Soft Computing10.1016/j.asoc.2012.11.04913:5(2412-2432)Online publication date: 1-May-2013
https://dl.acm.org/doi/10.1016/j.asoc.2012.11.049
Larrañaga PKarshenas HBielza CSantana R(2012)A review on probabilistic graphical models in evolutionary computationJournal of Heuristics10.1007/s10732-012-9208-418:5(795-819)Online publication date: 1-Oct-2012
https://dl.acm.org/doi/10.1007/s10732-012-9208-4
Gallagher M(2012)Beware the parametersProceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II10.1007/978-3-642-32964-7_48(478-487)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/978-3-642-32964-7_48
Kramer OGieseke F(2011)Variance scaling for EDAs revisitedProceedings of the 34th Annual German conference on Advances in artificial intelligence10.5555/2051037.2051053(169-178)Online publication date: 4-Oct-2011
https://dl.acm.org/doi/10.5555/2051037.2051053
Pošík PPelikan MBranke J(2010)Stochastic local search in continuous domainsProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830830(1937-1944)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830830
Yang DJiao LGong MFeng H(2009)Hybrid multiobjective estimation of distribution algorithm by local linear embedding and an immune inspired algorithmProceedings of the Eleventh conference on Congress on Evolutionary Computation10.5555/1689599.1689659(463-470)Online publication date: 18-May-2009
https://dl.acm.org/doi/10.5555/1689599.1689659
Pošík PRothlauf F(2009)BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distributionProceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers10.1145/1570256.1570322(2309-2314)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1570256.1570322
Valdez-Peña SHernández-Aguirre ABotello-Rionda SRothlauf F(2009)Approximating the search distribution to the selection distribution in EDAsProceedings of the 11th Annual conference on Genetic and evolutionary computation10.1145/1569901.1569965(461-468)Online publication date: 8-Jul-2009
https://dl.acm.org/doi/10.1145/1569901.1569965
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