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Improving an interior-point approach for large block-angular problems by hybrid preconditioners

Autor
Bocanegra, S.; Castro, J.; Oliveira, A.R.L.
Tipus d'activitat
Article en revista
Revista
European journal of operational research
Data de publicació
2013-12
Volum
231
Número
2
Pàgina inicial
263
Pàgina final
273
DOI
https://doi.org/10.1016/j.ejor.2013.04.007 Obrir en finestra nova
Projecte finançador
Group on Numerical Optimization and Modeling (SGR-2009-1122)
OPTIMIZACION DE MUY GRAN ESCALA PARA PRIVACIDAD DE DATOS
OPTIMIZACION DE PROBLEMAS ESTRUCTURADOS DE GRAN ESCALA. APLICACIONES A CONFIDENCIALIDAD DE DATOS.
URL
http://www.sciencedirect.com/science/article/pii/S0377221713003056 Obrir en finestra nova
Resum
The computational time required by interior-point methods is often dominated by the solution of linear systems of equations. An efficient specialized interior-point algorithm for primal block-angular problems has been used to solve these systems by combining Cholesky factorizations for the block constraints and a conjugate gradient based on a power series preconditioner for the linking constraints. In some problems this power series preconditioner resulted to be inefficient on the last interior-...
Paraules clau
Interior-point methods, Large-scale optimization, Preconditioned conjugate gradient, Structured problems
Grup de recerca
GNOM - Grup d'Optimització Numèrica i Modelització

Participants

  • Bocanegra, Silvana  (autor)
  • Castro Perez, Jordi  (autor)
  • Oliveira, Aurelio Ribeiro Leite  (autor)