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A nonmonotone conic trust region method based on line search for solving unconstrained optimization

✍ Scribed by Shao-Jian Qu; Qing-Pu Zhang; Yue-Ting Yang

Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
675 KB
Volume
224
Category
Article
ISSN
0377-0427

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✦ Synopsis

In this paper, we present a nonmonotone conic trust region method based on line search technique for unconstrained optimization. The new algorithm can be regarded as a combination of nonmonotone technique, line search technique and conic trust region method. When a trial step is not accepted, the method does not resolve the trust region subproblem but generates an iterative point whose steplength satisfies some line search condition. The function value can only be allowed to increase when trial steps are not accepted in close succession of iterations. The local and global convergence properties are proved under reasonable assumptions. Numerical experiments are conducted to compare this method with the existing methods.

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