Testing successive regression approximations by large-scale two-stage problems

István Deák ()

Annals of Operations Research, 2011, vol. 186, issue 1, 83-99

Abstract: A heuristic procedure, called successive regression approximations (SRA) has been developed for solving stochastic programming problems. They range from equation solving to probabilistic constrained and two-stage models through a combined model of Prékopa. We show here, that due to enhancements in the computer program, SRA can be used to solve large-scale two-stage problems with 100 first stage decision variables and a 120 dimensional normally distributed random right hand side vector in the second stage problem. A FORTRAN source program and computational results for 124 problems are presented at www.uni-corvinus.hu/~ideak1 . Copyright Springer Science+Business Media, LLC 2011

Date: 2011
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DOI: 10.1007/s10479-009-0602-8

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