This paper deals with particular families of DC optimization problems involving suprema convex functions. We show that the specific structure this type function allows us to cover a variety in nonconvex programming. Necessary and sufficient optimality conditions for these are established, where some structural features conveniently exploited. More precisely, we derive necessary (global local) s...

Interior point methods, the traditional methods for the SDP , are fairly limited in the size of problems they can handle. This paper deals with an LP approach to overcome some of these shortcomings. We begin with a semi-infinite linear programming formulation of the SDP and discuss the issue of its discretization in some detail. We further show that a lemma due Pataki on the geometry of the SDP...

In this paper, possibilistic linear programming problems are investigated. After reviewing relations among conjunction and implication functions, necessity fractile optimization models with various implication functions are applied to the possibilistic linear problems. We show that the necessity fractile optimization models are reduced to semi-infinite linear programming problems. A simple nume...