Towards a self-stopping evolutionary algorithm using coupling from the past

German Hernandez, Fernando Nino, Kenneth Wilder, Julian Garcia

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

In this paper a stopping criterion for a particular class of evolutionary algorithms is devised. First, a model of a generic evolutionary algorithm using iterated random maps is presented. The model allows the exploration of a connection between coupling from the past, and a stopping criterion for evolutionary algorithms. Accordingly, a method to stop a generic evolutionary algorithm is proposed. Some computational experiments are carried out to test the stopping criterion, using a modified version of coupling from the past. Empirical evidence is shown to support the suitability of the criterion.

Original languageEnglish
Title of host publicationGECCO 2005 - Genetic and Evolutionary Computation Conference
EditorsH.G. Beyer, U.M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E.W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, al et al
Pages615-620
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes
EventGECCO 2005 - Genetic and Evolutionary Computation Conference - Washington, D.C., United States of America
Duration: 25 Jun 200529 Jun 2005

Conference

ConferenceGECCO 2005 - Genetic and Evolutionary Computation Conference
CountryUnited States of America
CityWashington, D.C.
Period25/06/0529/06/05

Keywords

  • Coupling from the Past
  • Evolutionary Algorithms
  • Optimization
  • Stopping Criteria

Cite this

Hernandez, G., Nino, F., Wilder, K., & Garcia, J. (2005). Towards a self-stopping evolutionary algorithm using coupling from the past. In H. G. Beyer, U. M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E. W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, ... A. et al (Eds.), GECCO 2005 - Genetic and Evolutionary Computation Conference (pp. 615-620) https://doi.org/10.1145/1068009.1068112
Hernandez, German ; Nino, Fernando ; Wilder, Kenneth ; Garcia, Julian. / Towards a self-stopping evolutionary algorithm using coupling from the past. GECCO 2005 - Genetic and Evolutionary Computation Conference. editor / H.G. Beyer ; U.M. O'Reilly ; D. Arnold ; W. Banzhaf ; C. Blum ; E.W. Bonabeau ; E. Cantu-Paz ; D. Dasgupta ; K. Deb ; al et al. 2005. pp. 615-620
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Hernandez, G, Nino, F, Wilder, K & Garcia, J 2005, Towards a self-stopping evolutionary algorithm using coupling from the past. in HG Beyer, UM O'Reilly, D Arnold, W Banzhaf, C Blum, EW Bonabeau, E Cantu-Paz, D Dasgupta, K Deb & A et al (eds), GECCO 2005 - Genetic and Evolutionary Computation Conference. pp. 615-620, GECCO 2005 - Genetic and Evolutionary Computation Conference, Washington, D.C., United States of America, 25/06/05. https://doi.org/10.1145/1068009.1068112

Towards a self-stopping evolutionary algorithm using coupling from the past. / Hernandez, German; Nino, Fernando; Wilder, Kenneth; Garcia, Julian.

GECCO 2005 - Genetic and Evolutionary Computation Conference. ed. / H.G. Beyer; U.M. O'Reilly; D. Arnold; W. Banzhaf; C. Blum; E.W. Bonabeau; E. Cantu-Paz; D. Dasgupta; K. Deb; al et al. 2005. p. 615-620.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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AB - In this paper a stopping criterion for a particular class of evolutionary algorithms is devised. First, a model of a generic evolutionary algorithm using iterated random maps is presented. The model allows the exploration of a connection between coupling from the past, and a stopping criterion for evolutionary algorithms. Accordingly, a method to stop a generic evolutionary algorithm is proposed. Some computational experiments are carried out to test the stopping criterion, using a modified version of coupling from the past. Empirical evidence is shown to support the suitability of the criterion.

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Hernandez G, Nino F, Wilder K, Garcia J. Towards a self-stopping evolutionary algorithm using coupling from the past. In Beyer HG, O'Reilly UM, Arnold D, Banzhaf W, Blum C, Bonabeau EW, Cantu-Paz E, Dasgupta D, Deb K, et al A, editors, GECCO 2005 - Genetic and Evolutionary Computation Conference. 2005. p. 615-620 https://doi.org/10.1145/1068009.1068112