A quantile is a popular performance measure for a stochastic system to evaluate its
variability and risk. To reduce the risk, selecting the actions that minimize the tail quantiles of …

We consider the problem of evaluating risk for a system that is modeled by a complex
stochastic simulation with many possible input parameter values. Two sources of …

For complex stochastic systems, simulation can be used to study the system inherent risk
behaviors characterized by a sequence of percentiles. In this paper, we develop a Bayesian …

Cov= covariance B= the matrix of covariance between responses G (a, b)= Gaussian
process with follows mean a and variance bn= the number of observed samples p= the …

Although the mean is a widely-used performance measure for stochastic simulations, the
quantiles have become very attractive to measure the variability and the risk of the simulated …

Work in this dissertation is motivated by reducing the design cost at the early design stage
while maintaining high design accuracy throughout all design stages. It presents four key …

This thesis proposes three pieces of work on the Gaussian process (GP) model and GP-
based Bayesian optimization (BO) for stochastic simulations. Firstly, we propose a multi …