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Department of Mathematics,
University of California San Diego

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Center for Computational Mathematics Seminar

Li Wang

UCSD

Semidefinite Relaxations for Semi-Infinite Polynomial Programming

Abstract:

We study how to solve semi-infinite polynomial programming (SIPP) problems by semidefinite relaxation method. We first introduce two SDP relaxation methods for solving polynomial optimization problems with finitely many constraints. Then we propose an exchange algorithm with SDP relaxations to solve SIPP problems with compact index set. At last, we extend the proposed method to SIPP problems with noncompact index set via homogenization. Numerical results show that the algorithm is efficient in practice.

May 6, 2014

11:00 AM

AP&M 2402

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