Selecting the best stochastic system for large scale problems in DEDS Original Research Article

We consider the problem of selecting the stochastic system with the best expected performance measure, when the number of alternative systems is large. We consider the case of discrete event dynamic systems (DEDS) where the standard clock simulation technique can be used for simulating multiple systems using only one sample path. In this paper, we use a two-phase procedure that uses the standard clock simulation technique. In the first phase, we screen out non-competent alternatives and construct a confidence set that contains the best alternative with a pre-specified large probability. In the second phase, we use the indifference-zone ranking and selection procedure to select the best expected alternative among the survivals of the first phase. We implement this algorithm for solving a practical simulation optimization problem.