Relaxation Method for Large Scale Linear Programming Using Decomposition

Relaxation Method for Large Scale Linear Programming Using Decomposition

In this paper we propose a new decomposition method for large scale linear programming. This method dualizes an (arbitrary) subset of the constraints and then maximizes the resulting dual functional by dual ascent. The ascent directions are chosen from a finite set and are generated by a truncated version of the painted index algorithm [13]. Central to this method is the novel notion of (e,8)co...

Large-scale decomposition for successive quadratic programming

Solving Fuzzy Linear Fractional Programming Problem using LU Decomposition Method

A Decomposition Algorithm for Solving a Three Level Large Scale linear Programming Problem

This paper presents a three level large scale linear programming problem in which the objective functions at every level are to be maximized. A three level programming problem can be thought as a static version of the Stackelberg strategy. An algorithm for solving a three planner model and a solution method for treating this problem are suggested. At each level we attempt to optimize its proble...

A simplicial decomposition framework for large scale convex quadratic programming

In this paper, we analyze in depth a simplicial decomposition like algorithmic framework for large scale convex quadratic programming. In particular, we first propose two tailored strategies for handling the master problem. Then, we describe a few techniques for speeding up the solution of the pricing problem. We report extensive numerical experiments on both real portfolio optimization and gen...