AN INEXACT PERTURBED PATH-FOLLOWING METHOD FOR LAGRANGIAN DECOMPOSITION IN LARGE-SCALE SEPARABLE CONVEX OPTIMIZATION

This paper studies an inexact perturbed path-following algorithm in the framework of Lagrangian dual decomposition for solving large-scale separable convex programming problems. Unlike the exact versions considered in the literature, we propose to solve the primal subproblems inexactly up to a given accuracy. This leads to an inexactness of the gradient vector and the Hessian … Read more