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A sequential quadratic programming algorithm for nonlinear minimax problems

Published online by Cambridge University Press:  17 April 2009

Qing-Jie Hu
Affiliation:
Department of Information, Hunan Business College, 410205, Changsha, Peoples Republic China e-mail: [email protected]
Ju-Zhou Hu
Affiliation:
Institute of Applied Mathematics, Hunan University, 410082, Changsha, Peoples Republic of China
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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.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2007

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