Non-Monotone Conic Trust Region Method Combined with Line Search Strategy
Journal Title: Scholars Bulletin - Year 2017, Vol 3, Issue 10
Abstract
Abstract:In this paper, we propose a non-monotone adaptive trust region algorithm based on conic model for solving unconstrained optimization problems. Unlike the traditional non-monotone trust-region method, our proposed algorithm avoids resolving the sub-problem whenever a trial step is rejected. Instead, it performs a non-monotone Armijo-type line search in direction of the rejected trial step to construct a new point. The algorithm can be regarded as a combination of non-monotone, line search and conic trust region method. Theoretical analysis indicates that the new approach preserves the global convergence to the first-order critical points under classical assumptions. Keywords:Unconstrained optimization; Conic trust-region method; Armijo-type line search; Non-monotone technique; global convergence
Authors and Affiliations
Yunfeng Zhang, Qinghua Zhou
Keywords
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