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SIAM Journal on Optimization, 2002
Summary: We present an algorithm that achieves superlinear convergence for nonlinear programs satisfying the Mangasarian--Fromovitz constraint qualification and the quadratic growth condition. This convergence result is obtained despite the potential lack of a locally convex augmented Lagrangian.
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Summary: We present an algorithm that achieves superlinear convergence for nonlinear programs satisfying the Mangasarian--Fromovitz constraint qualification and the quadratic growth condition. This convergence result is obtained despite the potential lack of a locally convex augmented Lagrangian.
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Sequential Quadratic Programming Design of Gear Transmission
Applied Mechanics and Materials, 2013The optimization design of gear transmission based on MATLAB is studied for the purpose of finding a convenient and practical method. A mathematical model of optimization design is established in order to minimize the volume of gear transmission, the sequential quadratic programming method (SQP) is used to solve the nonlinear constrained optimization ...
Zi Bin Xu, Jian Qing Min
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Inexact Sequential Quadratic Programming
2013In this chapter we develop a novel approach for the solution of inequality constrained optimization problems. We first describe inexact Newton methods in Section 5.1 and investigate their local convergence in Section 5.2. In Section 5.3 we review strategies for the globalization of convergence and explain a different approach based on generalized level
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Sequential Quadratic Programming Method of Cabin Optimization
Applied Mechanics and Materials, 2014The basic principle of sequential quadratic programming method and the concrete implementation steps in MATLAB are expounded. Sequential quadratic programming method is used for the cabin structure optimization. In the optimization, the minimal sizes of components stipulated by the rules are used as size constraints, the frequencies required by the ...
Han Liu +3 more
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The Sequential Quadratic Programming Method
2010Sequential (or Successive) Quadratic Programming (SQP) is a technique for the solution of Nonlinear Programming (NLP)problems. It is, as we shall see, an idealized concept, permitting and indeed necessitating many variations and modifications before becoming available as part of a reliable andefficient production computer code.
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Sequential Quadratic Programming Methods for Large-Scale Problems
Computational Optimization and Applications, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sequential Quadratic Programming in Banach Spaces
1992We analyze a sequential quadratic programming method for optimization problems in Banach spaces. We give sufficient conditions for local quadratic convergence of the method. The results are applied to various optimization problems.
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