Fast simulation of rare events in queueing and reliability models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Iterative methods for solving linear systems
Iterative methods for solving linear systems
An efficient disk-based tool for solving large Markov models
Performance Evaluation - Special issue on tools for performance evaluation
Stochastic processes
Waiting time, busy periods and output models of a server analyzed via Wiener-Hopf factorization
Performance Evaluation - Special issue on performance and control of network systems
Multilevel Splitting for Estimating Rare Event Probabilities
Operations Research
WSC '83 Proceedings of the 15th conference on Winter Simulation - Volume 2
Computation of the Asymptotic Bias and Variance for Simulation of Markov Reward Models
SS '96 Proceedings of the 29th Annual Simulation Symposium (SS '96)
Optimal service rates for the state-dependent M/G/1 queues in steady state
Operations Research Letters
Warm-up periods in simulation can be detrimental
Probability in the Engineering and Informational Sciences
When, and when not to use warm-up periods in discrete event simulation
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Rethinking the initialization bias problem in steady-state discrete event simulation
Proceedings of the Winter Simulation Conference
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Simulating continuous-time Markov reward processes containing rarely visited, but economically important states requires long simulation times unless special measures are taken. In this article, we consider Markov reward processes in equilibrium, and we use the equilibrium equations to reallocate rewards. The effect of this reallocation is determined analytically for a number of small examples. In these examples, significant savings in run lengths were possible, especially in the case where the expected rewards are strongly influenced by low-probability boundary states. The emphasis of the article is on exploration; no large simulation problems have been considered.