R. Enkhbat, T. Bayartugs
School of Mathematics and Computer Sciences
National University of Mongolia
P.O. Box 46/635, Ulaanbaatar, 210646, MONGOLIA
School of Mathematics
Mongolian University of Science and Technology

Abstract. We introduce so-called semidefinite quasiconcave programming or equivalently semidefinite quasiconvex maximization problem. We derive new global optimality conditions by generalizing [#!ref:no1!#]. Based on the global optimality conditions, we construct an algorithm which generates a sequence of local maximizers that converges to a global solution. Subproblems of the proposed algorithm are semidefinite linear programming.

Received: May 23, 2013

AMS Subject Classification: 52A41

Key Words and Phrases: semidefinite linear programming, global optimality conditions, semidefinite concave programming, algorithm, approximation set

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