Abstract
This paper presents a comparison of the performance of four different sampling methods used in stochastic simulation. The methods are crude Monte Carlo sampling, median LHS, Halton sequence and a new method based on gaussian quadrature. A model of a batch distillation column is used to compare the accuracy and the convergence properties of the various methods. The results show that the quadrature method is superior the others in this example. A convergence rate up to 1250 times faster than of MC sampling is found.
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