Learning to Simulate: Generative Metamodeling via Quantile Regression
Stochastic simulation models effectively capture complex system dynamics but are often too slow for real-time decision-making. Traditional metamodeling techniques learn …
L. Jeff Hong
Professor in Department of Industrial and Systems Engineering at the University of Minnesota.
Staffing Under Taylor's Law: A Unifying Framework for Bridging Square-Root and Linear Safety Rules
Staffing rules serve as an essential management tool in service industries to attain target service levels. Traditionally, the square-root safety rule, based on the Poisson arrival …
Knowledge Gradient for Selection with Covariates: Consistency and Computation
Knowledge gradient is a design principle for developing Bayesian sequential sampling policies to consider in this paper the ranking and selection problem in the presence of …
Surrogate-Based Simulation Optimization
Simulation models are widely used in practice to facilitate decision making in a complex, dynamic and stochastic environment. But they are computationally expensive to execute and …
Ranking and Selection with Covariates for Personalized Decision Making
We consider a ranking and selection problem in the context of personalized decision making, where the best alternative is not universal but varies as a function of observable …
Distributionally Robust Selection of the Best
Specifying a proper input distribution is often a challenging task in simulation modeling. In practice, there may be multiple plausible distributions that can fit the input data …
Enhancing Stochastic Kriging for Queueing Simulation with Stylized Models
Stochastic kriging is a popular metamodeling technique to approximate computationally expensive simulation models. However, it typically treats the simulation model as a black box …
Ranking and Selection with Covariates
We consider a new ranking and selection problem in which the performance of each alternative depends on some observable random covariates. The best alternative is thus not constant …
Scaling and Modeling of Call Center Arrivals
The Poisson process has been an integral part of many models for the arrival process to a telephone call centers. However, several publications in recent years suggest the presence …
Robust Selection of the Best
Classical ranking-and-selection (R&S) procedures cannot be applied directly to select the best decision in the presence of distributional ambiguity. In this paper we propose a …