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A rounding procedure for semidefinite optimization

Ali Mohammad-Nezhad (alm413***at***lehigh.edu)
Tamas Terlaky (terlaky***at***lehigh.edu)

Abstract: Recently, Mohammad-Nezhad and Terlaky studied the identification of the optimal partition for semidefinite optimization. An approximation of the optimal partition was obtained from a bounded sequence of solutions on, or in a neighborhood of the central path. Here, we use the approximation of the optimal partition in a rounding procedure to generate an approximate maximally complementary solution. The procedure generates a rounded primal-dual solution from an interior solution, sufficiently close to the optimal set, by solving two least square problems.

Keywords: Semidefinite optimization, Optimal partition, Interior point methods, Maximally complementary solution

Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Citation: Technical report 17T-009, Industrial and Systems Engineering, Lehigh University, May 28, 2017

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Entry Submitted: 07/03/2017
Entry Accepted: 07/03/2017
Entry Last Modified: 05/28/2018

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