The inverse problem in convex optimization with linear constraints

Abstract

In this paper, we solve an inverse problem arising in convex optimization. We consider a maximization problem under m linear constraints. We characterize the solutions of this kind of problems. More precisely, we give necessary and sufficient conditions for a given function in Rn to be the solution of a multi-constraint maximization problem. The conditions we give here extend well-known results in microeconomic theory