DocumentCode :
1637600
Title :
A Modified Filter Trust Region Method for Nonlinear Programming
Author :
Ke, Su
Author_Institution :
Tongji Univ., Shanghai
fYear :
2007
Firstpage :
287
Lastpage :
290
Abstract :
Sequential quadratic programming (SQP) type method is one of the most effective methods for solving nonlinear programming. Recently, filter method, for its good numerical results, are extensively studied to handle nonlinear programming problems. In this paper, a new modified approach combined the filter technique and SQP trust region method is proposed to tackle the original problem, which ensures that every trail point will not be far away from the feasible region. Global convergence results of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.
Keywords :
filtering theory; nonlinear programming; numerical analysis; quadratic programming; modified filter trust region method; nonlinear programming; sequential quadratic programming; Constraint optimization; Convergence; Educational institutions; Electronic mail; Filters; Functional programming; Lagrangian functions; Mathematical programming; Mathematics; Quadratic programming; Filter Method; Nonlinear Programming; Sequential Quadratic Programming; Trust Region;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
Type :
conf
DOI :
10.1109/CHICC.2006.4346770
Filename :
4346770
Link To Document :
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