A practical update criterion for SQP method

DOI10.1080/10556780500474915zbMath1130.90056OpenAlexW2029622466MaRDI QIDQ5758221

Tao-Wen Liu, Dong-hui Li

Publication date: 3 September 2007

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556780500474915

zbMATH Keywords

global convergencealgorithm updatecriterionequality contrained optimizationsequrntial quadratic programming

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Methods of quasi-Newton type (90C53) Research exposition (monographs, survey articles) pertaining to operations research and mathematical programming (90-02) Methods of successive quadratic programming type (90C55)

Related Items (3)

A new regularized limited memory BFGS-type method based on modified secant conditions for unconstrained optimization problems ⋮ A superlinearly convergent SQP method without boundedness assumptions on any of the iterative sequences ⋮ A reduced Hessian SQP method for inequality constrained optimization

Cites Work

• Exact penalty function algorithm with simple updating of the penalty parameter
• An analysis of reduced Hessian methods for constrained optimization
• On the Global Convergence of the BFGS Method for Nonconvex Unconstrained Optimization Problems
• A Strategy for Global Convergence in a Sequential Quadratic Programming Algorithm
• A recursive quadratic programming algorithm that uses differentiable exact penalty functions
• A Tool for the Analysis of Quasi-Newton Methods with Application to Unconstrained Minimization
• Convergence of the BFGS Method for $LC^1 $ Convex Constrained Optimization
• On the Local Convergence of Quasi-Newton Methods for Constrained Optimization
• Practical Update Criteria for Reduced Hessian SQP: Global Analysis
• On the Local and Superlinear Convergence of Quasi-Newton Methods
• On the Sequential Quadratically Constrained Quadratic Programming Methods
• Definite and Semidefinite Quadratic Forms

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