nonlinear minimax problems
Recently Published Documents


TOTAL DOCUMENTS

13
(FIVE YEARS 0)

H-INDEX

6
(FIVE YEARS 0)

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Daolan Han ◽  
Jinbao Jian ◽  
Qinfeng Zhang

The nonlinear minimax problems without constraints are discussed. Due to the expensive computation for solving QP subproblems with inequality constraints of SQP algorithms, in this paper, a QP-free algorithm which is also called sequential systems of linear equations algorithm is presented. At each iteration, only two systems of linear equations with the same coefficient matrix need to be solved, and the dimension of each subproblem is not of full dimension. The proposed algorithm does not need any penalty parameters and barrier parameters, and it has small computation cost. In addition, the parameters in the proposed algorithm are few, and the stability of the algorithm is well. Convergence property is described and some numerical results are provided.



2009 ◽  
Vol 144 (2) ◽  
pp. 291-318 ◽  
Author(s):  
E. Obasanjo ◽  
G. Tzallas-Regas ◽  
B. Rustem


2008 ◽  
Vol 205 (1) ◽  
pp. 247-262 ◽  
Author(s):  
Mian-Tao Chao ◽  
Zhong-Xing Wang ◽  
Yu-Mei Liang ◽  
Qing-Jie Hu


2008 ◽  
Vol 164 (1) ◽  
pp. 167-191 ◽  
Author(s):  
Fusheng Wang ◽  
Kecun Zhang


2007 ◽  
Vol 76 (3) ◽  
pp. 353-368 ◽  
Author(s):  
Qing-Jie Hu ◽  
Ju-Zhou Hu

In this paper, an active set sequential quadratic programming algorithm with non-monotone line search for nonlinear minmax problems is presented. At each iteration of the proposed algorithm, a main search direction is obtained by solving a reduced quadratic program which always has a solution. In order to avoid the Maratos effect, a correction direction is yielded by solving the reduced system of linear equations. Under mild conditions without the strict complementarity, the global and superlinear convergence can be achieved. Finally, some preliminary numerical experiments are reported.





2006 ◽  
Vol 73 (1) ◽  
pp. 117-127 ◽  
Author(s):  
Jin-Bao Jian ◽  
Ran Quan ◽  
Xue-Lu Zhang

In this paper, nonlinear minimax problems are discussed. Using Sequential Quadratic Programming and the generalised monotone line search technique, we propose a new algorithm for solving degenerate minimax problems. At each iteration of the proposed algorithm, a search direction is obtained by solving a new Quadratic Programming problem which always has a solution. Global convergence can be obtained without the regularity condition of linear independence. Finally, some numerical experiments are reported.



Sign in / Sign up

Export Citation Format

Share Document