Abstract
We describe a statistical procedure for testing the quality of a feasible candidate solut ion for an important class of stochastic programs. Quality is defined via the so-called optimality gap and th e procedure’s output is a confidence interval on this gap. We review a multiple-replications procedure for constructing the confidence interval. Then, we present a result that allows the procedure to be computationally simplified to a single-replication procedure.
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Morton, D.P. (2003). Testing Solution Quality in Stochastic Programs. In: Leopold-Wildburger, U., Rendl, F., Wäscher, G. (eds) Operations Research Proceedings 2002. Operations Research Proceedings 2002, vol 2002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55537-4_64
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DOI: https://doi.org/10.1007/978-3-642-55537-4_64
Publisher Name: Springer, Berlin, Heidelberg
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