Optimal computing budget allocation with exponential underlying distribution

In this paper, we consider the simulation budget allocation problem to maximize the probability of selecting the best simulated design in ordinal optimization. This problem has been studied extensively on the basis of the normal distribution. In this research, we consider the budget allocation problem when the underlying distribution is exponential. This case is widely seen in simulation practice. We derive an asymptotic closed-form allocation rule which is easy to compute and implement in practice, and provide some useful insights for the optimal budget allocation problem with exponential underlying distribution.