Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4641178 | Journal of Computational and Applied Mathematics | 2009 | 11 Pages |
Abstract
We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
C. Bogani, M.G. Gasparo, A. Papini,