Document Zbl 1406.65043

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Several guaranteed descent conjugate gradient methods for unconstrained optimization. (English) Zbl 1406.65043

J. Appl. Math. 2014, Article ID 825958, 14 p. (2014).

Summary: This paper investigates a general form of guaranteed descent conjugate gradient methods which satisfies the descent condition \(g^T_k d_k\leq -(1-1/(4\theta_k))\| g_k\|^2\) (\(\theta_k>1/4\)) and which is strongly convergent whenever the weak Wolfe line search is fulfilled. Moreover, we present several specific guaranteed descent conjugate gradient methods and give their numerical results for large-scale unconstrained optimization.

MSC:

65K05	Numerical mathematical programming methods
90C26	Nonconvex programming, global optimization
90C52	Methods of reduced gradient type

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