Optimization for Sparse Systems.

Sparse matrices with special structure arise in almost every application of large scale optimization. In linear programming, these problems usually are solved by pivoting procedures, most notably the simplex method, refined and modified in various ways to exploit structure. More recently iterative relaxation methods and dual ascent algorithms have been proposed for certain applications. In surveying several algorithms from each of these categories, this paper demonstrates the potential for investigating and applying sparse system techniques in optimization. Author