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Sequential Quadratic Programming *

Published online by Cambridge University Press:  07 November 2008

Paul T. Boggs
Affiliation:
Applied and Computational Mathematics DivisionNational Institute of Standards and TechnologyGaithersburg, Maryland 20899USA E-mail: boggs@cam.nist.gov
Jon W. Tolle
Affiliation:
Departments of Mathematics and Operations ResearchUniversity of North CarolinaChapel Hill, North Carolina 27599USA E-mail: tolle@math.unc.edu

Extract

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.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

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