Numerical experiences with a new generalized subinterval selection criterion for interval global optimization

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

The convergence properties are studied for interval global optimization algorithms that select the next subinterval to be subdivided with the largest value of the indicator pf(fk, X) = fk-F(X)/F(X)-F(X). In contrast to previous work, here the more general case is investigated, when the global minimum value is unknown, and thus its estimation fk in the iteration k has an important role. Extensive numerical tests on 40 problems confirm that substantial improvements can be achieved both on simple and sophisticated algorithms by the new method (not utilizing the minimum value).

Original languageEnglish
Pages (from-to)109-125
Number of pages17
JournalReliable Computing
Volume9
Issue number2
DOIs
Publication statusPublished - Apr 2003

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Global Minimum
Global optimization
Convergence Properties
Global Optimization
Optimization Algorithm
Iteration
Unknown
Interval
Experience

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

Cite this

Numerical experiences with a new generalized subinterval selection criterion for interval global optimization. / Csendes, T.

In: Reliable Computing, Vol. 9, No. 2, 04.2003, p. 109-125.

Research output: Contribution to journalArticle

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