Heuristic rejection in interval global optimization

L. G. Casado, I. García, T. Csendes, V. G. Ruíz

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Based on the investigation carried out in Ref. 1, this paper incorporates new studies about the properties of inclusion functions on subintervals while a branch-and-bound algorithm is solving global optimization problems. It is found that the relative place of the global minimum value within the inclusion function value of the objective function at the current interval indicates mostly whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a considerable amount of computation. Illustrative examples are discussed and an extended numerical study shows the advantages of the new approach.

Original languageEnglish
Pages (from-to)27-43
Number of pages17
JournalJournal of Optimization Theory and Applications
Volume118
Issue number1
DOIs
Publication statusPublished - Jul 2003

Fingerprint

Global optimization
Rejection
Global Optimization
Heuristics
Interval
Inclusion
Branch and Bound Algorithm
Global Minimum
Minimizer
Value Function
Numerical Study
Objective function
Optimization Problem
Optimization problem
Branch and bound algorithm
Value function

Keywords

  • Branch-and-bound algorithms
  • Global optimization
  • Interval method

ASJC Scopus subject areas

  • Applied Mathematics
  • Control and Optimization
  • Management Science and Operations Research

Cite this

Heuristic rejection in interval global optimization. / Casado, L. G.; García, I.; Csendes, T.; Ruíz, V. G.

In: Journal of Optimization Theory and Applications, Vol. 118, No. 1, 07.2003, p. 27-43.

Research output: Contribution to journalArticle

Casado, L. G. ; García, I. ; Csendes, T. ; Ruíz, V. G. / Heuristic rejection in interval global optimization. In: Journal of Optimization Theory and Applications. 2003 ; Vol. 118, No. 1. pp. 27-43.
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