Large-scale Optimization

Decomposition methods aim to reduce large-scale problems to simpler problems. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. Block problems in which the coupling variables do not enter the binding constraints are studied.