Article ID: | iaor20003060 |
Country: | Netherlands |
Volume: | 11 |
Issue: | 3 |
Start Page Number: | 277 |
End Page Number: | 296 |
Publication Date: | Dec 1998 |
Journal: | Computational Optimization and Applications |
Authors: | Barrientos O. |
Keywords: | optimization, computational analysis |
A method is presented for solving the finite nonlinear min–max problem. Quasi-Newton methods are used to approximately solve a sequence of differentiable subproblems where, for each subproblem, the cost function to minimize is a global regularization underestimating the finite maximum function. Every cluster point of the sequence generated is shown to be a stationary point of the min–max problem and therefore, in the convex case, to be a solution of the problem. Moreover, numerical results are given for a large set of test problems which show that the method is efficient in practice.