Maximization of lower semi-continuous convex functional on bounded subsets of locally convex spaces. II: Quasi-Lagrangian duality theorems
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Abstract
We prove, for a proper lower semi-continuous convex functional ƒ on a locally convex space E and a bounded subset G of E, a formula for sup ƒ(G) which is symmetric to the Lagrange multiplier theorem for convex minimization, obtained in [7], with the difference that for sup ƒ(G) Lagrange multiplier functionals need not exist. When ƒ is also continuous we give some necessary conditions for g0 ∈ G to satisfy ƒ(g0) = sup ƒ(G). Also, we give some applications to deviations and farthest points. Finally, we show the connections with the “hyperplane theorems” of our previous paper [8].
Keywords
Lagrange Multiplier Convex Subset Penalty Term Duality Theorem Convex Space
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References
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© Birkhäuser Verlag, Basel 1980