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A conjugate gradient method with descent direction for unconstrained optimization

✍ Scribed by Gonglin Yuan; Xiwen Lu; Zengxin Wei

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
726 KB
Volume
233
Category
Article
ISSN
0377-0427

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✦ Synopsis

A modified conjugate gradient method is presented for solving unconstrained optimization problems, which possesses the following properties: (i) The sufficient descent property is satisfied without any line search; (ii) The search direction will be in a trust region automatically; (iii) The Zoutendijk condition holds for the Wolfe-Powell line search technique; (iv) This method inherits an important property of the well-known Polak-Ribière-Polyak (PRP) method: the tendency to turn towards the steepest descent direction if a small step is generated away from the solution, preventing a sequence of tiny steps from happening. The global convergence and the linearly convergent rate of the given method are established. Numerical results show that this method is interesting.

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