The infinite dimensional Lagrange multiplier rule for convex optimization problems

AbstractIn this paper an infinite dimensional generalized Lagrange multipliers rule for convex optimization problems is presented and necessary and sufficient optimality conditions are given in order to guarantee the strong duality. Furthermore, an application is presented, in particular the existence of Lagrange multipliers associated to the bi-obstacle problem is obtained

Convex separable problems with linear and box constraints

In this work, we focus on separable convex optimization problems with linear and box constraints and compute the solution in closed-form as a function of some Lagrange multipliers that can be easily computed in a finite number of iterations. This allows us to bridge the gap between a wide family of power allocation problems of practical interest in signal processing and communications and their efficient implementation in practice.Comment: 5 pages, 2 figures. Published at IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014