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.
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Research supported by National Scientific Research Fund (Hungary), grant T047340.
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Deák, I. Testing successive regression approximations by large-scale two-stage problems. Ann Oper Res 186, 83–99 (2011). https://doi.org/10.1007/s10479-009-0602-8
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DOI: https://doi.org/10.1007/s10479-009-0602-8