A New Non-monotone Self-Adaptive Trust Region Method with Fixed Step-size for Unconstrained Optimization
Journal Title: Scholars Journal of Engineering and Technology - Year 2015, Vol 3, Issue 5
Abstract
In this paper, we propose and analyze a new non-monotone self-adaptive trust region method with fixed step-size for unconstrained optimization. Unlike the traditional non-monotone trust region method, our algorithm utilizes a fixed formula to get the next iterative point if a trial step is not adopted. Besides, the trust region radius of related sub-problem adjusts itself adaptively. By the above techniques, we can decrease the number of solving sub-problems efficiently. Under some standard assumptions, we show that the new proposed method has a global convergence. Keywords: unconstrained optimization, non-monotone technique, self-adaptive trust region method, fixed step-size, global convergence
Authors and Affiliations
Changyuan Li, Qinghua Zhou
Keywords
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