An improved sequential quadratic programming algorithm for inequality constrained optimization

An improved sequential quadratic programming algorithm for inequality constrained optimization

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Article ID: iaor20051142
Country: Germany
Volume: 58
Issue: 2
Start Page Number: 271
End Page Number: 282
Publication Date: Jan 2003
Journal: Mathematical Methods of Operations Research (Heidelberg)
Authors: , ,
Abstract:

In this paper, the feasible type SQP method is improved. A new algorithm is proposed to solve nonlinear inequality constrained problem, in which a new modified method is presented to decrease the computational complexity. It is required to solve only one QP subproblem with only a subset of the constraints estimated as active per single iteration. Moreover, a direction is generated to avoid the Maratos effect by solving a system of linear equations. The theoretical analysis shows that the algorithm has global and superlinear convergence under some suitable conditions. In this end, numerical experiments are given to show that the method in this paper is effective.

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