An efficient sequential quadratic programming algorithm for nonlinear programming

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Abstract

In this paper, a new feasible sequential quadratic programming (FSQP) algorithm is proposed to solve the nonlinear programming, where a feasible descent direction is obtained by solving only one QP subproblem. In order to avoid Maratos effect, a high-order revised direction is computed by solving a linear system with involving some "active"; constraints. The theoretical analysis shows that global and superlinear convergence can be deduced. © 2004 Elsevier B.V. All rights reserved.

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APA

Zhu, Z. (2005). An efficient sequential quadratic programming algorithm for nonlinear programming. Journal of Computational and Applied Mathematics, 175(2), 447–464. https://doi.org/10.1016/j.cam.2004.07.001

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