A hybrid descent method for global optimization

Yiu, C, Liu, Y and Teo, K 2004, 'A hybrid descent method for global optimization', Journal of Global Optimization, vol. 28, no. 2, pp. 229-238.

Document type: Journal Article
Collection: Journal Articles

Title A hybrid descent method for global optimization
Author(s) Yiu, C
Liu, Y
Teo, K
Year 2004
Journal name Journal of Global Optimization
Volume number 28
Issue number 2
Start page 229
End page 238
Total pages 9
Publisher Springer New York LLC
Abstract In this paper, a hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm is used to locate descent points for previously converged local minima. The combined method has the descent property and the convergence is monotonic. To demonstrate the effectiveness of the proposed hybrid descent method, several multi-dimensional non-convex optimization problems are solved. Numerical examples show that global minimum can be sought via this hybrid descent method.
Subject Operations Research
Keyword(s) descent method
global minimum
simulating annealing
DOI - identifier 10.1023/B:JOGO.0000015313.93974.b0
Copyright notice © 2004 Kluwer Academic Publishers
ISSN 0925-5001
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Citation counts: Scopus Citation Count Cited 56 times in Scopus Article | Citations
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