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Global convergence of a new method for Minimax problem without a penalty function or a filter
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhao, Qi Zhang, Yan |
| Copyright Year | 2012 |
| Abstract | We present a class of trust region algorithm that do not use any penalty function or a filter for unconstrained minimax optimization problems. Using the slack variables,we turn the original problem into a nonlinear programming with equality constraints and simple bounds. In each iteration, the infeasibility is controlled by a progressively decreasing upper limit and trial steps are computed by a Byrd-Omojokun-type trust region strategy. Measures of optimality and infeasibility are computed, whose relationship serves as a criterion on which the algorithm decides which one to focus on improving. The algorithm ensure the global convergence without assuming the LICQ qualification. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.sajm-online.com/uploads/sajm2-2-3.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
