Intelligent exploration for genetic algorithms

Using self-organizing maps in evolutionary computation

Hani Ben Amor, Achim Rettinger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

46 Citations (Scopus)

Abstract

Exploration vs. exploitation is a well known issue in Evolutionary Algorithms. Accordingly, an unbalanced search can lead to premature convergence. GASOM, a novel Genetic Algorithm, addresses this problem by intelligent exploration techniques. The approach uses Self-Organizing Maps to mine data from the evolution process. The information obtained is successfully utilized to enhance the search strategy and confront genetic drift. This way, local optima are avoided and exploratory power is maintained. The evaluation of GASOM on well known problems shows that it effectively prevents premature convergence and seeks the global optimum. Particularly on deceptive and misleading functions it showed outstanding performance. Additionally, representing the search history by the Self-Organizing Map provides a visually pleasing insight into the state and course of evolution.

Original languageEnglish (US)
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
Pages1531-1538
Number of pages8
DOIs
StatePublished - 2005
Externally publishedYes
EventGECCO 2005 - Genetic and Evolutionary Computation Conference - Washington, D.C., United States
Duration: Jun 25 2005Jun 29 2005

Other

OtherGECCO 2005 - Genetic and Evolutionary Computation Conference
CountryUnited States
CityWashington, D.C.
Period6/25/056/29/05

Fingerprint

Self organizing maps
Evolutionary algorithms
Genetic algorithms

Keywords

  • Diversity
  • Exploration vs. Exploitation
  • Genetic Algorithm
  • Genetic Drift
  • Premature Convergence
  • Self-Organizing Map

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Ben Amor, H., & Rettinger, A. (2005). Intelligent exploration for genetic algorithms: Using self-organizing maps in evolutionary computation. 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. 1531-1538) https://doi.org/10.1145/1068009.1068250

Intelligent exploration for genetic algorithms : Using self-organizing maps in evolutionary computation. / Ben Amor, Hani; Rettinger, Achim.

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. 1531-1538.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ben Amor, H & Rettinger, A 2005, Intelligent exploration for genetic algorithms: Using self-organizing maps in evolutionary computation. 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. 1531-1538, GECCO 2005 - Genetic and Evolutionary Computation Conference, Washington, D.C., United States, 6/25/05. https://doi.org/10.1145/1068009.1068250
Ben Amor H, Rettinger A. Intelligent exploration for genetic algorithms: Using self-organizing maps in evolutionary computation. 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. 1531-1538 https://doi.org/10.1145/1068009.1068250
Ben Amor, Hani ; Rettinger, Achim. / Intelligent exploration for genetic algorithms : Using self-organizing maps in evolutionary computation. 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. 1531-1538
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