Abstract
Sufficiency and necessity theorems are described which test the optimality of a vector when it is required to minimize a given function of variables which are subject to inequalities. The paper starts with an exposition of theorems of alternatives, which are fundamental when the functions considered are linear, and proceeds to a systematic formulation of various constraint qualifications, which make it possible to extend results which hold in linear programming to the non-linear case.

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