DocumentCode
2122327
Title
A new algorithm based on rSQP and AD
Author
Li, Jin ; Tan, Yuejin ; Liao, Liangcai
Author_Institution
Dept. of Manage., Nat. Univ. of Defense Technol., Hunan
fYear
0
fDate
0-0 0
Lastpage
5
Abstract
An efficient optimization algorithm based on reduced sequential quadratic programming (rSQP) and automatic differentiation (AD) is presented in this paper. With the characteristics of sparseness, relatively low degrees of freedom and equality constraints utilized, the nonlinear programming problem was solved by improved rSQP solver. In the solving process, AD technology was used to obtain accurate gradient information. The numerical results show that the combined algorithm, which is suitable for large-scale process optimization problems, can calculate more efficiently than rSQP itself
Keywords
quadratic programming; automatic differentiation; large-scale process optimization problems; nonlinear programming problem; optimization algorithm; reduced sequential quadratic programming; Design engineering; Design optimization; Finite difference methods; Information management; Large-scale systems; Management information systems; Optimization methods; Quadratic programming; Quality management; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Control Applications, 2005. ICIECA 2005. International Conference on
Conference_Location
Quito
Print_ISBN
0-7803-9419-4
Type
conf
DOI
10.1109/ICIECA.2005.1644342
Filename
1644342
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