Reliability and Performance of UEGO, a Clustering-based global Optimizer

Pilar M. Ortigosa, I. García, M. Jelasity

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

UEGO is a general clustering technique capable of accelerating and/or parallelizing existing search methods. UEGO is an abstraction of GAS, a genetic algorithm (GA) with subpopulation support, so the niching (i.e. clustering) technique of GAS can be applied along with any kind of optimizers, not only genetic algorithm. The aim of this paper is to analyze the behavior of the algorithm as a function of different parameter settings and types of functions and to examine its reliability with the help of Csendes' method. Comparisons to other methods are also presented.

Original languageEnglish
Pages (from-to)265-289
Number of pages25
JournalJournal of Global Optimization
Volume19
Issue number3
DOIs
Publication statusPublished - Mar 2001

Fingerprint

Genetic algorithms
Genetic Algorithm
Clustering
Niching
genetic algorithm
Search Methods
subpopulation
method
Genetic algorithm
Abstraction
parameter
comparison

Keywords

  • Evolutionary algorithms
  • Global optimization
  • Stochastic optimization

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Global and Planetary Change
  • Applied Mathematics
  • Control and Optimization

Cite this

Reliability and Performance of UEGO, a Clustering-based global Optimizer. / Ortigosa, Pilar M.; García, I.; Jelasity, M.

In: Journal of Global Optimization, Vol. 19, No. 3, 03.2001, p. 265-289.

Research output: Contribution to journalArticle

Ortigosa, Pilar M. ; García, I. ; Jelasity, M. / Reliability and Performance of UEGO, a Clustering-based global Optimizer. In: Journal of Global Optimization. 2001 ; Vol. 19, No. 3. pp. 265-289.
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