A descent nonlinear conjugate gradient method for large-scale unconstrained optimization. (English) Zbl 1117.65097

Author’s summary: A new nonlinear conjugate gradient method is proposed for large-scale unconstrained optimization which possesses the following three properties: (i) the sufficient descent property holds without any line searches; (ii) employing some steplength technique which ensures the Zoutendijk condition to be held, this method is globally convergent; (iii) this method inherits an important property of the 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. Preliminary numerical results show that this method is very promising.


65K05 Numerical mathematical programming methods
90C06 Large-scale problems in mathematical programming
90C30 Nonlinear programming


Full Text: DOI


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