This paper concerns applications of advanced techniques of variational analysis and generalized differentiation to parametric problems of semi-infinite and infinite programming, where decision variables run over finite-dimensional and infinite-dimensional spaces, respectively. Part I is primarily devoted to the study of robust Lipschitzian stability of feasible solutions maps for such problems ...

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...

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...

There are two interesting methods, in the literature, for solving fuzzy linear programming problems in which the elements of coefficient matrix of the constraints are represented by real numbers and rest of the parameters are represented by symmetric trapezoidal fuzzy numbers. The first method, named as fuzzy primal simplex method, assumes an initial primal basic feasible solution is at hand. T...

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...