Under a Bayesian framework, we formulate the fully sequential sampling and selection
decision in statistical ranking and selection as a stochastic control problem, and derive the …

In this note, we consider the statistical ranking and selection problem of finding the best
alternative when the performances of each alternative must be estimated by sampling. We …

Simulation is often used to estimate the performance of alternative system designs for
selecting the best. For a complex system, high-fidelity simulation is usually time-consuming …

We review static and dynamic optimization formulations for simulation allocation and
selection procedures and revisit several sampling approaches under a single umbrella. We …

In this note, we study a simulation optimization problem of selecting the alternative with the
best performance from a finite set, or a so-called ranking and selection problem, in a special …

Monte Carlo simulation is a commonly used tool for evaluating the performance of complex
stochastic systems. In practice, simulation can be expensive, especially when comparing a …

We consider the problem of selecting the best alternative in a setting where prior similarity
information between the performance output of different alternatives can be learned from …

We propose a dynamic sampling allocation and selection paradigm for finding the
alternative with the optimal quantile in a Bayesian framework. Myopic allocation policies …

This paper introduces a new perspective on the problem of finite sample Ranking and
Selection. An asymptotically equivalent approximation to the probability of correct selection …

We study a ranking and selection problem with exponential sampling distributions. Under a
Bayesian framework, we derive the posterior distribution of the performance parameter, and …