Global and local convergence of a filter line search method for nonlinear programming

DOI10.1080/10556780600565489zbMath1193.90192OpenAlexW2142906186MaRDI QIDQ5436909

Khalid Mohamed Nor, Choong Ming Chin, Abdul Halim Abdul Rashid

Publication date: 18 January 2008

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

Full work available at URL: https://doi.org/10.1080/10556780600565489

zbMATH Keywords

superlinear convergence

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Methods of successive quadratic programming type (90C55)

Related Items (13)

A dwindling filter trust region algorithm for nonlinear optimization ⋮ A line search filter-SQP method with Lagrangian function for nonlinear inequality constrained optimization ⋮ Global and local convergence of a new affine scaling trust region algorithm for linearly constrained optimization ⋮ A new penalty-free-type algorithm based on trust region techniques ⋮ A penalty-free method with superlinear convergence for equality constrained optimization ⋮ A filter algorithm for nonlinear systems of equalities and inequalities ⋮ A modified filter SQP method as a tool for optimal control of nonlinear systems with spatio-temporal dynamics ⋮ Global and local convergence of a class of penalty-free-type methods for nonlinear programming ⋮ An inexact secant algorithm for large scale nonlinear systems of equalities and inequalities ⋮ A penalty-free method with line search for nonlinear equality constrained optimization ⋮ A line search SQP method without a penalty or a filter ⋮ Some results on the filter method for nonlinear complementary problems ⋮ An infeasible QP-free method without a penalty function for nonlinear inequality constrained optimization

Uses Software

• ipfilter

Cites Work

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• On the global convergence of an SLP-filter algorithm that takes EQP steps
• Non-monotone trust region methods for nonlinear equality constrained optimization without a penalty function
• On the convergence of Newton iterations to non-stationary points
• Interior-point methods for nonconvex nonlinear programming: Filter methods and merit functions
• A globally convergent primal-dual interior-point filter method for nonlinear programming
• On the superlinear local convergence of a filter-SQP method
• On combining feasibility, descent and superlinear convergence in inequality constrained optimization
• On uniqueness of Kuhn-Tucker multipliers in nonlinear programming
• A two-stage feasible directions algorithm for nonlinear constrained optimization
• A Superlinearly Convergent Feasible Method for the Solution of Inequality Constrained Optimization Problems
• Reduced quasi-Newton methods with feasibility improvement for nonlinearly constrained optimization
• A surperlinearly convergent algorithm for constrained optimization problems
• The watchdog technique for forcing convergence in algorithms for constrained optimization
• Nonlinear programming via an exact penalty function: Asymptotic analysis
• Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms
• A necessary and sufficient regularity condition to have bounded multipliers in nonconvex programming
• An Algorithm for Minimax Solution of Overdetermined Systems of Non-linear Equations
• A Nonmonotone Line Search Technique for Newton’s Method
• On the Global Convergence of a Filter--SQP Algorithm
• Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming
• Line Search Filter Methods for Nonlinear Programming: Local Convergence
• Nonlinear programming without a penalty function.

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