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An active set sequential quadratic programming algorithm for nonlinear optimisation

Published online by Cambridge University Press:  17 April 2009

Qing-Jie Hu ,
Yun-Hai Xiao  and
Y. Chen
Qing-Jie Hu
Affiliation:
Institute of Applied Mathematics, Hunan University, 410082 Changsha, Peoples Republic China, Department of Information, Hunan Business College, 410205 Changsha, Peoples Republic of China, e-mail: [email protected]
Yun-Hai Xiao
Affiliation:
Institute of Applied Mathematics, Hunan University, 410082 Changsha, Peoples Republic China
Y. Chen
Affiliation:
Department of Information, Hunan Business College, 410205 Changsha, Peoples Republic of China
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In this paper, we have proposed an active set feasible sequential quadratic programming algorithm for nonlinear inequality constraints optimization problems. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a reduced quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving a reduced least square problem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions without strict complementarity.

Type
Research Article
Information
Bulletin of the Australian Mathematical Society , Volume 74 , Issue 1 , August 2006 , pp. 69 - 83
Copyright
Copyright © Australian Mathematical Society 2006

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