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Introduction to Mathematical Programs with Cone Complementarity Constraints

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Abstract:
Semidefinite programs (SDPs) - optimization problems involving symmetric positive semidefinite matrix variables - are well studied for instance in engineering control and structural mechanics. Mathematical programs with semidefinite complementarity constraints are nonconvex optimization problems arise, eg, as inverse problems when the forward model is an SDP. Analogous to standard mathematical programs with complementarity constraints, in which the variables are nonnegative & orthogonal vectors, the complementarity (orthogonality) constraint will be treated via a penalty in the objective function. The resulting problem is a nonlinear and nonconvex optimization problem with matrix (and vector) variables and constraints. We will present a simple form of the problem and analyse it's stationary conditions. Then we will use an application from structural optimization solve this numerically using the code PENNON. Co-author: Michal Kocvara, The University of Birmingham, School of Mathematics, kocvara@maths.bham.ac.uk

http://www.jbs.cam.ac.uk/research/faculty/ralphd.html
Type of Seminar:
Optimization and Applications Seminar
Speaker:
Prof. Daniel Ralph
University of Cambridge, Judge Business School
Date/Time:
Mar 29, 2010   16:30
Location:

HG G 19.1, Rämistrasse 101
Contact Person:

Prof. J. Lygeros
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