scholarly journals Superlinearly convergent quasi-newton algorithms for nonlinearly constrained optimization problems

1976 ◽  
Vol 11 (1) ◽  
pp. 1-13 ◽  
Author(s):  
U. M. Garcia Palomares ◽  
O. L. Mangasarian
Keyword(s):  
Constrained Optimization ◽  
Optimization Problems ◽  
Constrained Optimization Problems ◽  
Nonlinearly Constrained Optimization ◽  
Quasi Newton

Sequential Quadratic Programming

Acta Numerica ◽  
1995 ◽  
Vol 4 ◽  
pp. 1-51 ◽  
Author(s):  
Paul T. Boggs ◽  
Jon W. Tolle
Keyword(s):  
Quadratic Programming ◽  
Constrained Optimization ◽  
Sequential Quadratic Programming ◽  
Large Scale ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Public Domain ◽  
Large Set ◽  
Constrained Optimization Problems ◽  
Nonlinearly Constrained Optimization

Since its popularization in the late 1970s, Sequential Quadratic Programming (SQP) has arguably become the most successful method for solving nonlinearly constrained optimization problems. As with most optimization methods, SQP is not a single algorithm, but rather a conceptual method from which numerous specific algorithms have evolved. Backed by a solid theoretical and computational foundation, both commercial and public-domain SQP algorithms have been developed and used to solve a remarkably large set of important practical problems. Recently large-scale versions have been devised and tested with promising results.

Sign in / Sign up

Export Citation Format

Share Document