R. Enkhbat, M. Bellalij, K. Jbilou, T. Bayartugs, “A method for semidefinite quasiconvex maximization problem”, Bulletin of Irkutsk State University. Series Mathematics, 2016, Volume 18,Pages <nobr>110

A method for semidefinite quasiconvex maximization problem

R. Enkhbat^a, M. Bellalij^b, K. Jbilou^c, T. Bayartugs^d

^a Institute of Mathematics, National University of Mongolia
^b University of Valenciennes and Hainaut-Cambresis, Departement des Mathematiques, Valenciennes, Nord-Pas-de-Calais, France
^c University of Littoral Côte d'Opale, Calais, France
^d University of Science and Technology, Mongolia

Abstract: We introduce so-called semidefinite quasiconvex maximization problem. We derive new global optimality conditions by generalizing [9]. Using these conditions, we construct an algorithm which generates a sequence of local maximizers that converges to a global solution. Also, new applications of semidefinite quasiconvex maximization are given. Subproblems of the proposed algorithm are semidefinite linear programming.

Keywords: semidefinite linear programming, global optimality conditions, semidefinite quasiconvex maximization, algorithm, approximation set.

UDC: 519.853

MSC: 90C26, 93C05

Language: English