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A new interior-point approach for large two-stage stochastic problems

Author
Castro, J.; de la Lama, P.
Type of activity
Report
Date
2020-04
Code
UPC-DEIO-JC DR 2020-01
Project funding
Modelling and optimization of large-scale structured problems and applications
Repository
http://hdl.handle.net/2117/184307 Open in new window
URL
http://www-eio.upc.edu/~jcastro/publications/reports/dr2020-01.pdf Open in new window
Abstract
Two-stage stochastic models give rise to very large optimization problems. Several approaches havebeen devised for efficiently solving them, including interior-point methods (IPMs). However, usingIPMs, the linking columns associated to first-stage decisions cause excessive fill-in for the solutionof the normal equations. This downside is usually alleviated if variable splitting is applied to first-stage variables. This work presents a specialized IPM that applies variable splitting and exploits ...
Citation
Castro, J.; de la Lama, P. "A new interior-point approach for large two-stage stochastic problems". 2020.
Keywords
Interior-point methods, Large-scale optimization, Stochastic optimization, Structured problems
Group of research
GNOM - Mathematical Optimization Group

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