Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24911
Title: A hybrid descent method for global optimization
Authors: Yiu, KFC
Liu, Y
Teo, KL
Keywords: Descent method
Global minimum
Simulating annealing
Issue Date: 2004
Publisher: Kluwer Academic Publ
Source: Journal of global optimization, 2004, v. 28, no. 2, p. 229-238 How to cite?
Journal: Journal of global optimization 
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.
URI: http://hdl.handle.net/10397/24911
ISSN: 0925-5001
EISSN: 1573-2916
DOI: 10.1023/B:JOGO.0000015313.93974.b0
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