Abstract
A saddle-point duality is proposed for the quasi-concave non-differentiable case of the maximization of the minimum between a finite number of functions. This class of problems contains quasi-concave (convex) programs that are known to be irreducible to convex ones. With the aid of the saddle-point duality involving conjugate-like operators, a Lagrangian is presented, the saddle-points of which give the exact global solutions. A few particular cases are discussed, among them the Von Neumann economic model and discrete rational approximation.
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Flachs, J. Global saddle-point duality for quasi-concave programs, II. Mathematical Programming 24, 326–345 (1982). https://doi.org/10.1007/BF01585114
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DOI: https://doi.org/10.1007/BF01585114