A Non-Monotone Trust Region Method with Non-Monotone Wolfe-Type Line Search Strategy for Unconstrained Optimization

Xiao  Wu; Qinghua  Zhou; Changyuan  Li

doi:10.4236/jamp.2015.36084

Changyuan Li^*, Qinghua Zhou^*, Xiao Wu

Abstract: In this paper, we propose and analyze a non-monotone trust region method with non-monotone line search strategy for unconstrained optimization problems. Unlike the traditional non-monotone trust region method, our algorithm utilizes non-monotone Wolfe line search to get the next point if a trial step is not adopted. Thus, it can reduce the number of solving sub-problems. Theoretical analysis shows that the new proposed method has a global convergence under some mild conditions.

Keywords: Unconstrained Optimization, Non-Monotone Trust Region Method, Non-Monotone Line Search, Global Convergence

Cite this paper: Li, C. , Zhou, Q. and Wu, X. (2015) A Non-Monotone Trust Region Method with Non-Monotone Wolfe-Type Line Search Strategy for Unconstrained Optimization. Journal of Applied Mathematics and Physics, 3, 707-712. doi: 10.4236/jamp.2015.36084.

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