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2010•Journal of North University of ChinaRequires access

Multiple-Cut Algorithm for Semidefinite Feasibility Problem

Xuewen Mu

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Abstract

To solve the semidefinite feasibility problem,it is more efficient to apply the analytic center cutting plane method than to convert it a semidefinite programming problem.A multiple-cut algorithm for the problem was proposed by improving the single-cut algorithm.Its convergence was discussed.The conclusion is proved that it is a quadratic convergent method.

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What this paper is about

To solve the semidefinite feasibility problem,it is more efficient to apply the analytic center cutting plane method than to convert it a semidefinite programming problem.A multiple-cut algorithm for the problem was proposed by improving the single-cut algorithm.Its convergence was discussed.The conclusion is proved that it is a quadratic convergent method.

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Available abstract

To solve the semidefinite feasibility problem,it is more efficient to apply the analytic center cutting plane method than to convert it a semidefinite programming problem.A multiple-cut algorithm for the problem was proposed by improving the single-cut algorithm.Its convergence was discussed.The conclusion is proved that it is a quadratic convergent method.

Key concepts: Semidefinite embedding, Semidefinite programming, Cutting-plane method, Quadratically constrained quadratic program, Maximum cut, Convergence (economics), Algorithm, Mathematics

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