Convergence of the Nonmonotone Perry and Shanno Method for Optimization

Authors:
Guanghui Liu;Lili Jing
Affiliations:
Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois, 60208, USA;College of Economics and Management, Beijing Forestry University, Beijing, 100083, People's Republic of China
Venue:
Computational Optimization and Applications
Year:
2000

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Abstract

In this paper a new nonmonotone conjugate gradient method is introduced, which can be regarded as a generalization of the Perry and Shanno memoryless quasi-Newton method. For convex objective functions, the proposed nonmonotone conjugate gradient method is proved to be globally convergent. Its global convergence for non-convex objective functions has also been studied. Numerical experiments indicate that it is able to efficiently solve large scale optmization problems.