A nonmonotone adaptive trust region method for unconstrained optimization based on conic model
نویسندگان
چکیده
In this paper, we present a nonmonotone adaptive trust region method for unconstrained optimization based on conic model. The new method combines nonmonotone technique and a new way to determine trust region radius at each iteration. The local and global convergence properties are proved under reasonable assumptions. Numerical experiments show that our algorithm is effective.
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ورودعنوان ژورنال:
- Applied Mathematics and Computation
دوره 217 شماره
صفحات -
تاریخ انتشار 2010