A large scale approach to decomposition spaces

A Decomposition-Coordination Approach for Large-Scale Optimization

A conic IPM decomposition approach for large scale

We describe a conic interior point decomposition approach for solving a large scale semidefinite program (SDP) whose primal feasible set is bounded. The idea is to solve such an SDP using existing primal-dual interior point methods, in an iterative fashion between amaster problem and a subproblem. In our case, the master problem is a mixed conic problem over linear and smaller sized semidefinit...

A dimensional decomposition approach to identifying efficient units in large-scale DEA models

In this paper, we propose the use of a dimensional decomposition procedure together with lexicographic parametric programming to reduce computational burden when identifying the efficient decision making units in Data Envelopment Analysis (DEA). The use of lexicographic parametric programming makes it possible to develop an efficient algorithm for the problems with few inputs and outputs. That’...

A Time Scale Decomposition Approach to Adaptive ECN Marking

Fair resource allocation in high-speed networks such as the Internet can be viewed as a constrained optimization program. Kelly and his co-workers have shown that an unconstrained penalty function formulation of this problem can be used to design congestion controllers that are stable. In this paper, we examine the question of providing feedback from the network such that the congestion control...

A limited memory adaptive trust-region approach for large-scale unconstrained optimization

This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newt...