Constrained nonlinear least squares: an exact penalty approach with projected structured quasi-Newton updates

DOI10.1145/66888.66891zbMath0900.65181OpenAlexW2063358067MaRDI QIDQ4371623

Nezam Mahdavi-Amiri, Richard H. Bartels

Publication date: 4 February 1998

Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)

Full work available at URL: http://www.acm.org/pubs/contents/journals/toms/1989-15/

zbMATH Keywords

nonlinear least squaresexact penalty methodconstrained nonlinear programmingstructured projected Hessian updates

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

Related Items (10)

Convergence theory for the structured BFGS secant method with an application to nonlinear least squares ⋮ A robust combined trust region–line search exact penalty projected structured scheme for constrained nonlinear least squares ⋮ A regularization method for constrained nonlinear least squares ⋮ Using a spectral scaling structured BFGS method for constrained nonlinear least squares ⋮ Superlinearly convergent exact penalty methods with projected structured secant updates for constrained nonlinear least squares ⋮ Gauss-Newton methods with approximate projections for solving constrained nonlinear least squares problems ⋮ Operations research and optimization (ORO) ⋮ A two-step superlinearly convergent projected structured BFGS method for constrained nonlinear least squares ⋮ Adaptive algorithm for constrained least-squares problems ⋮ Exploiting additional structure in equality constrained optimization by structured SQP secant algorithms

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