A hybrid global optimization algorithm involving simplex and inductive search

Chetan Offord, Željko Bajzer

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

19 Scopus citations

Abstract

We combine the recently proposed inductive search and the Nelder-Mead simplex method to obtain a hybrid global optimizer, which is not based on random searches. The global search is performed by line minimizations (Brent's method) and plane minimizations (simplex method), while the local multidimensional search employs the standard and a modified simplex method. Results for the test bed of the Second International Competition of Evolutionary Optimization and for another larger test bed show remarkable success. The algorithm was also effcient in minimizing functions related to energy of protein folding.

Original languageEnglish (US)
Title of host publicationComputational Science – ICCS 2001 - International Conference, Proceedings
EditorsVassil N. Alexandrov, Jack J. Dongarra, Benjoe A. Juliano, Rene S. Renner, C.J. Kenneth Tan
PublisherSpringer Verlag
Pages680-688
Number of pages9
ISBN (Print)3540422331, 9783540422334
DOIs
StatePublished - Jan 1 2001
EventInternational Conference on Computational Science, ICCS 2001 - San Francisco, United States
Duration: May 28 2001May 30 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2074
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Computational Science, ICCS 2001
CountryUnited States
CitySan Francisco
Period5/28/015/30/01

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Offord, C., & Bajzer, Ž. (2001). A hybrid global optimization algorithm involving simplex and inductive search. In V. N. Alexandrov, J. J. Dongarra, B. A. Juliano, R. S. Renner, & C. J. Kenneth Tan (Eds.), Computational Science – ICCS 2001 - International Conference, Proceedings (pp. 680-688). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2074). Springer Verlag. https://doi.org/10.1007/3-540-45718-6_73