DocumentCode
2571057
Title
A modified mnemonic enhancement optimization method for solving parametric nonlinear programming problems
Author
Wang, Zhiqiang ; Shao, Zhijiang ; Fang, Xueyi ; Chen, Weifeng ; Wan, Jiaona
Author_Institution
State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
fYear
2010
fDate
15-17 Dec. 2010
Firstpage
2210
Lastpage
2214
Abstract
A mnemonic enhancement optimization framework based on radial basis function (RBF-MEO), which is concerned with the application of RBF interpolation for generation of starting points in parametric nonlinear optimization, is studied in this work. Some theories of interior point algorithm support that the RBF-MEO method is very suitable for collaborating with interior point solvers, such as IPOPT. Numerical experiments illustrate that good accuracy and high rate of convergence are obtained by IPOPT with RBF-MEO.
Keywords
interpolation; nonlinear programming; radial basis function networks; IPOPT interior point solvers; RBF interpolation; RBF-MEO method; interior point algorithm; mnemonic enhancement optimization method; parametric nonlinear programming; radial basis function; Adaptation model; Biological system modeling; Computational modeling; Feeds; Interpolation; Optimization; Programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location
Atlanta, GA
ISSN
0743-1546
Print_ISBN
978-1-4244-7745-6
Type
conf
DOI
10.1109/CDC.2010.5717333
Filename
5717333
Link To Document