A class of nonmonotone Armijo-type line search method for unconstrained optimization
نویسندگان
چکیده
This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. In this article, we propose a new line search method for solving unconstrained optimization problems in that we combine a nonmonotone strategy into a modified Armijo rule and design a new algorithm that possibly chooses a larger steplength. This can decrease the number of iterations and function evaluations and can improve the efficiency of the algorithm. The global convergence and convergence rate are analysed under some suitable conditions. Preliminary numerical experiments establish that the new approach is robust and efficient for unconstrained optimization problems.
منابع مشابه
On efficiency of nonmonotone Armijo-type line searches
Abstract Monotonicity and nonmonotonicity play a key role in studying the global convergence and the efficiency of iterative schemes employed in the field of nonlinear optimization, where globally convergent and computationally efficient schemes are explored. This paper addresses some features of descent schemes and the motivation behind nonmonotone strategies and investigates the efficiency of...
متن کاملGlobal Convergence of a New Nonmonotone Algorithm
Abstract: In this study, we study the application of a kind of nonmonotone line search in BFGS algorithm for solving unconstrained optimization problems. This nonmonotone line search is belongs to Armijo-type line searches and when the step size is being computed at each iteration, the initial test step size can be adjusted according to the characteristics of objective functions. The global con...
متن کاملA nonmonotone truncated Newton-Krylov method exploiting negative curvature directions, for large scale unconstrained optimization
We propose a new truncated Newton method for large scale unconstrained optimization, where a Conjugate Gradient (CG)-based technique is adopted to solve Newton’s equation. In the current iteration, the Krylov method computes a pair of search directions: the first approximates the Newton step of the quadratic convex model, while the second is a suitable negative curvature direction. A test based...
متن کاملA Trust-region Method using Extended Nonmonotone Technique for Unconstrained Optimization
In this paper, we present a nonmonotone trust-region algorithm for unconstrained optimization. We first introduce a variant of the nonmonotone strategy proposed by Ahookhosh and Amini cite{AhA 01} and incorporate it into the trust-region framework to construct a more efficient approach. Our new nonmonotone strategy combines the current function value with the maximum function values in some pri...
متن کاملConvergence of Liu-storey Conjugate Method with Nonmonotone Armijo Line Search
In this paper, we develop a new nonmonotone Armijo-type line search for LS (Liu-Storey) conjugate gradient method for minimizing functions having Lipschitz continuous partial derivatives. The nonmonotone line search can guarantee the global convergence of original LS method under some mild conditions. AMS Subject Classification: 90C30, 65K05
متن کامل