Modified nonmonotone memory gradient method for unconstrained optimization

doi:10.3969/j.issn.1000-1565.2018.06.001

Abstract

Abstract: A modified nonmonotone line search memory gradient method for unconstrained optimization is proposed in this paper. In this method, a new criterion is constructed to decide whether the trial point is acceptable or not. The presented algorithm is a generalization of the existing nonmonotone-type methods. Under some reasonable conditions, the global convergent properties are proved. The numerical results show that the algorithm is effective and flexible.

Key words: unconstrained optimization, memory gradient methods, global convergence, nonmonotone

CLC Number:

O221.2

SU Ke, REN Lele, RONG Zixing, XU Chun. Modified nonmonotone memory gradient method for unconstrained optimization[J]. Journal of Hebei University (Natural Science Edition), 2018, 38(6): 561-566.

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