Decomposition based interior point methods for two-stage stochastic convex quadratic programs with recourse

Decomposition based interior point methods for two-stage stochastic convex quadratic programs with recourse

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Article ID: iaor200970271
Country: United States
Volume: 57
Issue: 4
Start Page Number: 964
End Page Number: 974
Publication Date: Jul 2009
Journal: Operations Research
Authors: ,
Keywords: interior point methods
Abstract:

Zhao showed that the log barrier associated with the recourse function of two-stage stochastic linear programs behaves as a strongly self-concordant barrier and forms a self-concordant family on the first-stage solutions. In this paper, we show that the recourse function is also strongly self-concordant and forms a self-concordant family for the two-stage stochastic convex quadratic programs with recourse. This allows us to develop Bender's decomposition based linearly convergent interior point algorithms. An analysis of such an algorithm is given in this paper.

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