This paper investigates the reduction of variance associated with a simulation output performance measure, using the Sequential Sampling method while applying minimum simulation replications, for a class of JIT (Just in Time) warehousing system called crossdocking. We initially used the Sequential Sampling method to attain a desired 95% confidence interval half width of ± 0.5 for our chosen per...

A total of 24 commercial fields of cabbages and Brussels sprouts were sampled in a grid fashion with 20-25 equally spaced cells with four plants per cell. Using this data base of 80-100 plants, we conducted computer stimulations to compare the treatment decisions that would be made for the major insect pests using published sequential sampling programs and a newly developed variable-intensity s...

sunn pest, eurygaster integriceps put., is the most important pest of wheat and barley in most producing regions of iran, including lorestan province. spatial distribution and fixed precision sequential sampling plans of sunn pest by the use of two quadrate sizes 0.25 and 0.5 m2 were investigated in rainfed wheat fields in borujerd during 2004 and 2005. based on r square of regression, taylor&a...

When observations are incomplete or data are missing, approximate inference methods based on importance sampling are often used. Unfortunately, when the target and proposal distributions are dissimilar, the sampling procedure leads to biased estimates or requires a prohibitive number of samples. Our method approximates a multivariate target distribution by sampling from an existing, sequential ...

The objective of this study is to develop a new modified Bayesian Kriging (MBKG) surrogate modeling method that can be used to carry out confidence-based reliability-based design optimization (RBDO) for problems in which simulation analyses are inherently noisy and standard Kriging approaches fail. The formulation of the MBKG surrogate modeling method is presented, and the full conditional dist...