A Global Convergence Analysis of an Algorithm for Large-Scale Nonlinear Optimization Problems

DOI10.1137/S1052623497316026zbMath0986.90078OpenAlexW1967581563MaRDI QIDQ4702312

Anthony José Kearsley, Paul T. Boggs, Jon W. Tolle

Publication date: 24 November 1999

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

Full work available at URL: https://doi.org/10.1137/s1052623497316026

zbMATH Keywords

global convergencesequential quadratic programmingnonlinear programmingmerit functionSQPlarge-scale problems

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Numerical methods based on nonlinear programming (49M37) Methods of successive quadratic programming type (90C55)

Related Items (13)

Sequential penalty algorithm for nonlinear constrained optimization ⋮ Pseudospectral methods based on nonclassical orthogonal polynomials for solving nonlinear variational problems ⋮ A hybrid approximation scheme for discretizing constrained quadratic optimal control problems ⋮ A primal-dual augmented Lagrangian ⋮ Smoothing augmented Lagrangian method for nonsmooth constrained optimization problems ⋮ Properties of a class of multilevel optimization algorithms for equality-constrained problems ⋮ Direct solution of a type of constrained fractional variational problems via an adaptive pseudospectral method ⋮ Global Convergence of a Trust Region Algorithm for Nonlinear Inequality Constrained Optimization Problems ⋮ A line search exact penalty method with bi-object strategy for nonlinear constrained optimization ⋮ A direct approach for the solution of nonlinear optimal control problems with multiple delays subject to mixed state-control constraints ⋮ Algorithms for optimal signal set design ⋮ Sequential quadratic programming for large-scale nonlinear optimization ⋮ A numerical method for mass spectral data analysis

Uses Software

• LANCELOT
• MINOS
• HQP/OMUSES

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