New concepts in nondifferentiable programming
New Farkas-type constraint qualifications in convex infinite programming
This paper provides KKT and saddle point optimality conditions, duality theorems and stability theorems for consistent convex optimization problems posed in locally convex topological vector spaces. The feasible sets of these optimization problems are formed by those elements of a given closed convex set which satisfy a (possibly infinite) convex system. Moreover, all the involved functions are assumed to be convex, lower semicontinuous and proper (but not necessarily real-valued). The key result...
Nonlinear Duality And Multiplier Theorems.
Nonparametric Maximum Likelihood Estimation of a Probability Density via Mathematical Programming.
Nonsmooth analysis and optimization on partially ordered vector spaces.