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A Hybrid Descent Method for Global Optimization

โœ Scribed by K.F.C. Yiu; Y. Liu; K.L. Teo


Book ID
111593099
Publisher
Springer US
Year
2004
Tongue
English
Weight
81 KB
Volume
28
Category
Article
ISSN
0925-5001

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In this paper, we propose two new hybrid nonlinear conjugate gradient methods, which produce sufficient descent search direction at every iteration. This property depends neither on the line search used nor on the convexity of the objective function. Under suitable conditions, we prove that the prop