A mixed superlinearly convergent algorithm with nonmonotone search for constrained optimizations

DOI10.1007/s11766-000-0028-1zbMath0970.90103OpenAlexW2086075137MaRDI QIDQ1576323

Wei Wang, Yi-Fan Xu

Publication date: 7 December 2000

Published in: Applied Mathematics. Series B (English Edition) (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11766-000-0028-1

zbMATH Keywords

sequential quadratic programmingconstrained optimizations

Mathematics Subject Classification ID

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

Related Items (4)

New sequential quadratically-constrained quadratic programming method of feasible directions and its convergence rate ⋮ A method combining norm-relaxed QP subproblems with systems of linear equations for constrained optimization ⋮ A new superlinearly convergent norm-relaxed method of strongly sub-feasible direction for inequality constrained optimization ⋮ A superlinearly convergent SQP method without boundedness assumptions on any of the iterative sequences

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
• 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
• Superlinearly convergent variable metric algorithms for general nonlinear programming problems
• A Nonmonotone Line Search Technique for Newton’s Method
• Sequential Quadratic Programming with Penalization of the Displacement

This page was built for publication: A mixed superlinearly convergent algorithm with nonmonotone search for constrained optimizations