Parallel Variable Distribution

New Inexact Parallel Variable Distribution Algorithms

We consider the recently proposed parallel variable distribution (PVD) algorithm of Ferris and Mangasarian [4] for solving optimization problems in which the variables are distributed among p processors. Each processor has the primary responsibility for updating its block of variables while allowing the remaining “secondary” variables to change in a restricted fashion along some easily computab...

Parallel Variable Distribution for Constrained Optimization

In the parallel variable distribution framework for solving optimization problems (PVD), the variables are distributed among parallel processors with each processor having the primary responsibility for updating its block of variables while allowing the remaining “secondary” variables to change in a restricted fashion along some easily computable directions. For constrained nonlinear programs c...

Parallel variable distribution for total least squares

A novel parallel method for determining an approximate total least squares (TLS) solution is introduced. Based on domain distribution, the global TLS problem is partitioned into several dependent TLS subproblems. A convergent algorithm using the parallel variable distribution technique (Ferris and Mangasarian, 1994) is presented. Numerical results support the development and analysis of the alg...

Parallel Variable Distribution Algorithm for Constrained Optimization with Nonmonotone Technique

On the Convergence of Constrained Parallel Variable Distribution Algorithms

We consider the parallel variable distribution (PVD) approach proposed by Ferris and Mangasarian [SIAM J. Optim., 4 (1994), pp. 815–832] for solving optimization problems. The problem variables are distributed among p processors with each processor having the primary responsibility for updating its block of variables while allowing the remaining “secondary” variables to change in a restricted f...