A feasible and superlinear algorithm for inequality constrained minimization problems

DOI10.1007/BF02670962zbMath0962.90047OpenAlexW1965274645MaRDI QIDQ1568229

Wei Wang, Yi-Fan Xu

Publication date: 24 June 2001

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02670962

zbMATH Keywords

global convergencesuperlinear convergencestrict complementary condition

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of successive quadratic programming type (90C55)

Cites Work

• Local analysis of Newton-type methods for variational inequalities and nonlinear programming
• Quadratically and superlinearly convergent algorithms for the solution of inequality constrained minimization problems
• On combining feasibility, descent and superlinear convergence in inequality constrained optimization
• A Superlinearly Convergent Feasible Method for the Solution of Inequality Constrained Optimization Problems
• A surperlinearly convergent algorithm for constrained optimization problems
• The watchdog technique for forcing convergence in algorithms for constrained optimization
• Generalized equations and their solutions, part II: Applications to nonlinear programming
• Avoiding the Maratos Effect by Means of a Nonmonotone Line Search. II. Inequality Constrained Problems—Feasible Iterates
• Superlinearly convergent variable metric algorithms for general nonlinear programming problems
• Sequential Quadratic Programming with Penalization of the Displacement