Feasible method for generalized semi-infinite programming

Feasible method for generalized semi-infinite programming

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Article ID: iaor20106182
Volume: 146
Issue: 2
Start Page Number: 419
End Page Number: 443
Publication Date: Aug 2010
Journal: Journal of Optimization Theory and Applications
Authors: ,
Keywords: Programming (semi-infinite)
Abstract:

In this paper, we analyze the outer approximation property of the algorithm for generalized semi-infinite programming from Stein and Still (2003). A simple bound on the regularization error is found and used to formulate a feasible numerical method for generalized semi-infinite programming with convex lower-level problems. That is, all iterates of the numerical method are feasible points of the original optimization problem. The new method has the same computational cost as the original algorithm from Stein and Still. We also discuss the merits of this approach for the adaptive convexification algorithm, a feasible point method for standard semi-infinite programming from Floudas and Stein (2007).

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