A quasi-Newton algorithm for semi-infinite programming using an Leo exact penalty function is described, and numerical results are presented. Comparisons with three Newton algorithms and one other quasi-Newton algorithm show that the algorithm is very promising in practice. AMS classifications: 65K05,90C30.

We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP ) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of co...

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...

The aim of this paper is to deal with a class of multiobjective semi-infinite programming problem. For such problem, several necessary optimality conditions are established and proved using the powerful tool of K − subdifferential and the generalized convexity namely generalized uniform ( , , , ) K F d α ρ − − convexity. We also formulate the Wolf type dual models for the semi-infinite programm...

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...