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
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;
Conference_Titel :
Industrial Electronics and Control Applications, 2005. ICIECA 2005. International Conference on
Conference_Location :
Quito
Print_ISBN :
0-7803-9419-4
DOI :
10.1109/ICIECA.2005.1644342
