# A heuristic rejection criterion in interval global optimization algorithms

L. G. Casado, I. García, T. Csendes

Research output: Contribution to journalArticle

18 Citations (Scopus)

### Abstract

This paper investigates the properties of the inclusion functions on subintervals while a Branch-and-Bound algorithm is solving global optimization problems. It has been found that the relative place of the global minimum value within the inclusion interval of the inclusion function of the objective function at the actual interval mostly indicates whether the given interval is close to a minimizer point. This information is used in a heuristic interval rejection rule that can save a big amount of computation. Illustrative examples are discussed and a numerical study completes the investigation.

Original language English 683-692 10 BIT Numerical Mathematics 41 4 Published - Dec 2001

### Fingerprint

Global optimization
Rejection
Global Optimization
Optimization Algorithm
Heuristics
Interval
Inclusion
Branch and Bound Algorithm
Global Minimum
Minimizer
Numerical Study
Objective function
Optimization Problem

### Keywords

• Branch-and-bound algorithm
• Global optimization
• Inclusion function

### ASJC Scopus subject areas

• Computer Graphics and Computer-Aided Design
• Software
• Applied Mathematics
• Computational Mathematics

### Cite this

A heuristic rejection criterion in interval global optimization algorithms. / Casado, L. G.; García, I.; Csendes, T.

In: BIT Numerical Mathematics, Vol. 41, No. 4, 12.2001, p. 683-692.

Research output: Contribution to journalArticle

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