Steady-state simulation of queueing processes: survey of problems and solutions
ACM Computing Surveys (CSUR)
Asymptotic formulas for Markov processes with applications to simulation
Operations Research
Stationarity detection in the initial transient problem
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
SS '96 Proceedings of the 29th Annual Simulation Symposium (SS '96)
Initial bias and estimation error in discrete event simulation
WSC '82 Proceedings of the 14th conference on Winter Simulation - Volume 2
Simulating markov-reward processes with rare events
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The art of simulation
Evaluation of methods used to detect warm-up period in steady state simulation
WSC '04 Proceedings of the 36th conference on Winter simulation
On an initial transient deletion rule with rigorous theoretical support
Proceedings of the 38th conference on Winter simulation
Warm-up periods in simulation can be detrimental
Probability in the Engineering and Informational Sciences
| Hi-index | 0.00 |
The state in which a discrete event simulation is started causes the estimators for equilibrium measures obtained from the simulation to be biased, and to reduce this bias, the collection of data is delayed until a so-called warm-up period is completed. In this paper, we determine the optimal warm-up periods for steady-state discrete event simulations. We do this by using deterministic numerical methods, that is, methods not using random numbers. We found that in the systems investigated, transient expectations give no indication regarding the optimal length of the warm-up periods, which is counterintuitive. This requires some re-evaluation of some of commonly held opinions about the factors one should take into account when determining warm-up periods. Such factors will also be discussed.