Artículos de revistas
A direct search method for nonlinear programming
Registro en:
Zeitschrift Fur Angewandte Mathematik Und Mechanik. Wiley-v C H Verlag Gmbh, v. 79, n. 4, n. 267, n. 276, 1999.
0044-2267
WOS:000079868600005
10.1002/(SICI)1521-4001(199904)79:4<267
Autor
Martinez, JM
Institución
Resumen
An iterative model algorithm Sbr minimizing a Lipschitz-continuous function subject to continuous constraints is introduced. Each iteration, of the method proceeds in two phases. In the first phase, feasibility is improved and, as a result, a more feasible intermediate point is obtained. In the second phase the algorithm tries to obtain a decrease of the objective function on an auxiliary feasible set. The output of the second phase is a trial point that is compared with the current iterate by means of a suitable merit function. If the merit function is sufficiently decreased, the trial point is accepted. Otherwise, it is rejected and the second phase is repeated in a reduced domain. Global convergence results are proved and practical applications are commented. 79 4 267 276