Variance within the manufacturing system leads to uneven shop loads, long manufacturing lead times, and unreliable customer service. This study compares techniques that reduce system variance to techniques that manage system variance. The study is placed in a dual resource constrained job shop. Results indicate that reducing system variance improves flow time and customer service performance me...

We develop strategies for integrated use of certain well-known variance reduction techniques to estimate a mean response in a finite-horizon simulation experiment. The building blocks for these integrated variance reduction strategies are the techniques of conditional expectation, correlation induction (including antithetic variates and Latin hypercube sampling), and control variates; and all p...

Monte Carlo simulations are a crucial tool for the analysis and prediction of various background components in liquid xenon (LXe) detectors. With improving shielding new experiments, simulation external backgrounds, such as induced by gamma rays from detector materials, gets more computationally expensive. We introduce validate an accelerated technique photon transport The method simulates phot...

T paper describes, analyzes and evaluates an algorithm for estimating portfolio loss probabilities using Monte Carlo simulation. Obtaining accurate estimates of such loss probabilities is essential to calculating value-at-risk, which is a quantile of the loss distribution. The method employs a quadratic (’’delta-gamma’’) approximation to the change in portfolio value to guide the selection of e...