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Journal of Convex Analysis 11 (2004), No. 2, 251--266
Copyright Heldermann Verlag 2004

Identifying Active Constraints via Partial Smoothness and Prox-Regularity

W. L. Hare
Dept. of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, whare@cecm.sfu.ca

A. S. Lewis
Dept. of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada, aslewis@sfu.ca

Active set algorithms, such as the projected gradient method in nonlinear optimization, are designed to "identify" the active constraints of the problem in a finite number of iterations. Using the notions of "partial smoothness" and "prox-regularity" we extend work of Burke, More and Wright on identifiable surfaces from the convex case to a general nonsmooth setting. We further show how this setting can be used in the study of sufficient conditions for local minimizers.

Keywords: nonlinear program, nonsmooth optimization, variational analysis, partly smooth, prox-regular, identifiable surface, projected gradient.

MSC 2000: 91C30, 49K40, 65K10.

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