UEGO, an abstract niching technique for global optimization

Research output: Conference contribution

15 Citations (Scopus)

Abstract

In this paper, UEGO, a new general technique for accelerating and/or parallelizing existing search methods is suggested. UEGO is a generalization and simplification of GAS, a genetic algorithm (GA) with subpopulation support. With these changes, the niching technique of GAS can be applied along with any kind of optimizers. Besides this, UEGO can be effectively parallelized. Empirical results are also presented which include an analysis of the effects of the user-given parameters and a comparison with a hill climber and a GA.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN 1998 - 5th International Conference, Proceedings
Pages378-387
Number of pages10
Publication statusPublished - dec. 1 1998
Event5th International Conference on Parallel Problem Solving from Nature, PPSN 1998 - Amsterdam, Netherlands
Duration: szept. 27 1998szept. 30 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1498 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Parallel Problem Solving from Nature, PPSN 1998
CountryNetherlands
CityAmsterdam
Period9/27/989/30/98

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Jelasity, M. (1998). UEGO, an abstract niching technique for global optimization. In Parallel Problem Solving from Nature, PPSN 1998 - 5th International Conference, Proceedings (pp. 378-387). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1498 LNCS).