This paper summarizes new analytical and empirical results for the economic approach to simulation selection problems that we introduced two years ago. The approach seeks to help managers to maximize the expected net present value (NPV) of system design decisions that are informed by simulation. It considers the time value of money, the cost of simulation sampling, and the time and cost of developing simulation tools. This economic approach to decision making with simulation is therefore an alternative to the statistical guarantees or probabilistic convergence results of other commonly-used approaches to simulation optimization. Empirical results are promising. This paper also retracts a claim that was made regarding the existence of Gittins' indices for these problems
Stephen E. Chick, Noah Gans