A penalty-interior-point algorithm for nonlinear constrained optimization

DOI10.1007/s12532-012-0041-4zbMath1269.49045OpenAlexW2085400344MaRDI QIDQ2392661

Frank E. Curtis

Publication date: 2 August 2013

Published in: Mathematical Programming Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s12532-012-0041-4

zbMATH Keywords

constrained optimizationlarge-scale optimizationnonlinear optimizationnonconvex optimizationinterior-point methodspenalty methodspenalty-interior-point methods

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Numerical methods involving duality (49M29) Numerical optimization and variational techniques (65K10) Numerical methods based on necessary conditions (49M05) Newton-type methods (49M15) Numerical methods based on nonlinear programming (49M37) Interior-point methods (90C51) Direct numerical methods for linear systems and matrix inversion (65F05) Numerical methods of relaxation type (49M20)

Related Items (13)

A primal-dual augmented Lagrangian penalty-interior-point filter line search algorithm ⋮ On the augmented subproblems within sequential methods for nonlinear programming ⋮ Learning to steer nonlinear interior-point methods ⋮ An augmented Lagrangian method for equality constrained optimization with rapid infeasibility detection capabilities ⋮ Worst-case complexity of an SQP method for nonlinear equality constrained stochastic optimization ⋮ An interior-point \(\ell_{\frac{1}{2}}\)-penalty method for inequality constrained nonlinear optimization ⋮ An overview of nonlinear optimization ⋮ Rapid infeasibility detection in a mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization ⋮ A globally convergent primal-dual interior-point relaxation method for nonlinear programs ⋮ A double-layer optimization model for flatness control of cold rolled strip ⋮ A primal-dual interior-point method capable of rapidly detecting infeasibility for nonlinear programs ⋮ A primal-dual interior-point relaxation method with global and rapidly local convergence for nonlinear programs ⋮ First- and second-order necessary conditions via exact penalty functions

Uses Software

• AMPL
• CUTEr
• SifDec
• Ipopt
• CUTE

Cites Work

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• A Modeling Language for Mathematical Programming
• Modified barrier functions (theory and methods)
• An interior-point algorithm for nonconvex nonlinear programming
• A modified barrier-augmented Lagrangian method for constrained minimization
• An improved branch and bound algorithm for mixed integer nonlinear programs
• A numerical study of limited memory BFGS methods
• Review of nonlinear mixed-integer and disjunctive programming techniques
• An algorithm for nonlinear optimization using linear programming and equality constrained subproblems
• Computational experience with penalty-barrier methods for nonlinear programming
• On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
• Interior-point \(\ell_2\)-penalty methods for nonlinear programming with strong global convergence properties
• Mathematical Programs with Complementarity Constraints: Stationarity, Optimality, and Sensitivity
• A Second Derivative SQP Method: Global Convergence
• Infeasibility Detection and SQP Methods for Nonlinear Optimization
• Steering exact penalty methods for nonlinear programming
• Adaptive Barrier Update Strategies for Nonlinear Interior Methods
• A modified barrier function method with improved rate of convergence for degenerate problems
• CUTE
• Interior Methods for Nonlinear Optimization
• Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence
• Primal–dual exterior point method for convex optimization
• CUTEr and SifDec
• On the Convergence of Successive Linear-Quadratic Programming Algorithms
• Interior Methods for Mathematical Programs with Complementarity Constraints
• A trust region method based on interior point techniques for nonlinear programming.
• Benchmarking optimization software with performance profiles.

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