New development of optimal computing budget allocation for discrete event simulation
Proceedings of the 29th conference on Winter simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization
Discrete Event Dynamic Systems
New Two-Stage and Sequential Procedures for Selecting the Best Simulated System
Operations Research
Optimal computing budget allocation for multi-objective simulation models
WSC '04 Proceedings of the 36th conference on Winter simulation
Optimal computing budget allocation under correlated sampling
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling
INFORMS Journal on Computing
| Hi-index | 0.00 |
Simulation is a popular tool for decision making. However, simulation efficiency is still a big concern particularly when multiple system designs must be simulated in order to find a best design. Simulation run allocation has emerged as an important research topic for simulation efficiency improvement. By allocating simulation runs in a more intelligent way, the total simulation time can be dramatically reduced. In this paper we develop a new simulation run allocation scheme. We compare the new approach with several different approaches. One benchmark approach assumes that the means and variances for all designs are known so that the theoretically optimal allocation can be found. It is interesting to observe that an approximation approach called OCBA does better than this theoretically optimal allocatio. Moreover, a randomized version of OCBA may outperform OCBA in some cases.