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Duality in quasi-convex supremization and reverse convex infimization via abstract convex analysis,and applications to approximation **
Abstract:We give duality theorems and dual characterizations of optimal solutions for abstract quasi-convex supremization problems and infimization problems with abstract reverse convex constraint sets. Our main tools are dualities between families of subsets, conjugations of type Lau associated to them, and subdifferentials with respect to conjugations of type Lau. These tools permit us to give explicitly the relation between.the constraint sets, and the relation between the objective functions, of the primal problem and the dual problem. As applications, we obtain duality theorems for quasi-convex supremization and reverse convex infimization in locally convex spaces and, in particular, for worst and best approximation in normed linear spaces.
Keywords:Quasi-convex Supremization  Reverse Convex Infimization  Abstract convex Analysis  Deviation  Farthest Point  Distance  Nearest Point
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