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    Variance reduction in Monte Carlo sampling-based optimality gap estimators for two-stage stochastic linear programming

    This paper presents a comparative computational study of the variance reduction techniques antithetic variates and Latin hypercube sampling when used for assessing solution quality in stochastic programming. T...

    Rebecca Stockbridge, Güzin Bayraksan in Computational Optimization and Applications (2016)