Complexity Analysis of a Trust Funnel Algorithm for Equality Constrained Optimization

DOI10.1137/16M1108650zbMath1391.49056arXiv1707.00337OpenAlexW2963059367MaRDI QIDQ4641670

Mohammadreza Samadi, Daniel P. Robinson, Frank E. Curtis

Publication date: 18 May 2018

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1707.00337

zbMATH Keywords

nonlinear optimizationnonconvex optimizationworst-case iteration complexityequality constrained optimizationtrust funnel methods

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Numerical mathematical programming methods (65K05) Abstract computational complexity for mathematical programming problems (90C60) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Newton-type methods (49M15) Numerical methods based on nonlinear programming (49M37) Complexity and performance of numerical algorithms (65Y20)

Related Items

Worst-case evaluation complexity of a quadratic penalty method for nonconvex optimization, A Newton-CG Based Augmented Lagrangian Method for Finding a Second-Order Stationary Point of Nonconvex Equality Constrained Optimization with Complexity Guarantees, Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization

Uses Software

• GQTPAR
• CUTEst

Cites Work

• Unnamed Item
• An interior-point trust-funnel algorithm for nonlinear optimization
• A trust region algorithm with a worst-case iteration complexity of \(\mathcal{O}(\epsilon ^{-3/2})\) for nonconvex optimization
• Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results
• Adaptive cubic regularisation methods for unconstrained optimization. II: Worst-case function- and derivative-evaluation complexity
• Nonlinear programming without a penalty function or a filter
• A constrained formulation of maximum-likelihood estimation for normal mixture distributions
• CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
• On the complexity of finding first-order critical points in constrained nonlinear optimization
• Cubic regularization of Newton method and its global performance
• Evaluation Complexity for Nonlinear Constrained Optimization Using Unscaled KKT Conditions and High-Order Models
• On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization
• A sequential quadratic programming algorithm with an additional equality constrained phase
• A second-derivative SQP method with a 'trust-region-free' predictor step
• An Inexact Sequential Quadratic Optimization Algorithm for Nonlinear Optimization
• A Second Derivative SQP Method: Global Convergence
• A Second Derivative SQP Method: Local Convergence and Practical Issues
• Optimal Solvers for PDE-Constrained Optimization
• On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming
• Computing a Trust Region Step
• A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians
• An Inexact SQP Method for Equality Constrained Optimization
• Trust Region Methods
• On High-order Model Regularization for Constrained Optimization
• An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity
• Real-Time PDE-Constrained Optimization
• Affine conjugate adaptive Newton methods for nonlinear elastomechanics
• Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part I: The Krylov--Schur Solver