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A new inexact SQP algorithm for nonlinear systems of mixed equalities and inequalities
Authors:Chao Gu  Detong Zhu  Yonggang Pei
Institution:1.School of Statistics and Mathematics,Shanghai Lixin University of Accounting and Finance,Shanghai,People’s Republic of China;2.Department of Mathematics,Shanghai Normal University,Shanghai,People’s Republic of China;3.College of Mathematics and Information Science,Henan Normal University,Xinxiang,China
Abstract:Traditional inexact SQP algorithm can only solve equality constrained optimization (Byrd et al. Math. Program. 122, 273–299 2010). In this paper, we propose a new inexact SQP algorithm with affine scaling technique for nonlinear systems of mixed equalities and inequalities, which arise in complementarity and variational inequalities. The nonlinear systems are transformed into a special nonlinear optimization with equality and bound constraints, and then we give a new inexact SQP algorithm for solving it. The new algorithm equipped with affine scaling technique does not require a quadratic programming subproblem with inequality constraints. The search direction is computed by solving one linear system approximately using iterative linear algebra techniques. Under mild assumptions, we discuss the global convergence. The preliminary numerical results show the effectiveness of the proposed algorithm.
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