Some numerical experience with a globally convergent algorithm for nonlinearly constrained optimization

1980 ◽  
Vol 32 (1) ◽  
pp. 1-16 ◽  
Author(s):  
I. D. Coope ◽  
R. Fletcher
Keyword(s):  
Constrained Optimization ◽  
Numerical Experience ◽  
Globally Convergent ◽  
Nonlinearly Constrained Optimization ◽  
Convergent Algorithm

scholarly journals A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Zhijun Luo ◽  
Lirong Wang
Keyword(s):  
Constrained Optimization ◽  
Optimization Problems ◽  
Linear Equations ◽  
Coefficient Matrix ◽  
Descent Direction ◽  
Constrained Optimization Problems ◽  
Inequality Constrained Optimization ◽  
Globally Convergent ◽  
Variable Distribution ◽  
Systems Of Linear Equations

A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved.

Sign in / Sign up

Export Citation Format

Share Document