The sparsity of solutions is a recurrent requirement in many applications of operations research. Many variables can be forced to be equal to zero by introducing l0-norm or l1-norm terms into optimization models.

In this thesis we would like to experiment with algorithmic procedures specifically designed to deal with l0 or l1 terms in the general case or in specific applications.

Algorithms for Sparse Optimization