Geodesic
A method for semidefinite quasiconvex maximization problem
The Bulletin of Irkutsk State University. Series Mathematics, Tome 18 (2016), pp. 110-121

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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. 
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     author = {R. Enkhbat and M. Bellalij and K. Jbilou and T. Bayartugs},
     title = {A method for semidefinite quasiconvex maximization problem},
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}
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R. Enkhbat; M. Bellalij; K. Jbilou; T. Bayartugs. A method for semidefinite quasiconvex maximization problem. The Bulletin of Irkutsk State University. Series Mathematics, Tome 18 (2016), pp. 110-121. http://geodesic.mathdoc.fr/item/IIGUM_2016_18_a7/