Journal of Global Optimization

, Volume 19, Issue 3, pp 265–289 | Cite as

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

  • Pilar M. Ortigosa
  • I. García
  • Márk Jelasity


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.

Global optimization Stochastic optimization Evolutionary algorithms 


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Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Pilar M. Ortigosa
    • 1
  • I. García
    • 1
  • Márk Jelasity
    • 2
  1. 1.Computer Architecture & Electronics DepartmentUniversity of Almería, Cta. Sacramento SNAlmeríaSpain
  2. 2.Research Group on Artificial Intelligence MTA-JATESzegedHungary

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