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A hybrid conjugate gradient method with descent property for unconstrained optimization. (English) Zbl 1432.90145
Summary: In this paper, based on some famous previous conjugate gradient methods, a new hybrid conjugate gradient method was presented for unconstrained optimization. The proposed method can generate decent directions at every iteration, moreover, this property is independent of the steplength line search. Under the Wolfe line search, the proposed method possesses global convergence. Medium-scale numerical experiments and their performance profiles are reported, which show that the proposed method is promising.

MSC:
90C30 Nonlinear programming
65K05 Numerical mathematical programming methods
90C52 Methods of reduced gradient type
Software:
CUTEr; minpack; CUTE
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References:
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