Modeling and simulation of biochemical systems are important tasks because they can provide insights into complicated systems where traditional experimentation is expensive or imp...
We formulate and evaluate distribution-free statistical process control (SPC) charts for monitoring an autocorrelated process when a training data set is used to estimate the marg...
Joongsup Lee, Christos Alexopoulos, David Goldsman...
Life cycle cost is an essential approach to decide on alternative rehabilitation strategies for infrastructure systems. Monte Carlo simulation approach is used to develop a stocha...
We investigate the use of Antithetic Variables, Control Variates and Importance Sampling to reduce the statistical errors of option sensitivities calculated with the Likelihood Ra...
There are two key issues in assuring the accuracy of estimates of performance obtained from a simulation model. The first is the removal of any initialisation bias, the second is ...
Currently, system engineering problems are solved using a wide range of domain-specific models and corresponding languages. It is unlikely that a single unified modeling language ...
We consider the ranking and selection of normal means in a fully sequential Bayesian context. By considering the sampling and stopping problems jointly rather than separately, we ...
Nowadays container terminals are struggling with a continuously increasing volume. Therefore, they are searching for solutions to increase throughput capacity without expanding th...
Simulation modeling methodology research and simulation analysis methodology research have evolved into two nearly separate fields. In this paper, ways are shown how simulation mi...