Simulation optimization using simultaneous replications and event time dilation
Proceedings of the 29th conference on Winter simulation
Sequential allocations that reduce risk for multiple comparisons
Proceedings of the 30th conference on Winter simulation
Computing budget allocation for simulation experiments with different system structure
Proceedings of the 30th conference on Winter simulation
Designing simultaneous simulation experiments
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Panel: future of simulation: panel session: the future of simulation
Proceedings of the 33nd conference on Winter simulation
Advanced event scheduling methodology: advanced event scheduling methodology
Proceedings of the 35th conference on Winter simulation: driving innovation
Analysis methodology: are we done?
WSC '05 Proceedings of the 37th conference on Winter simulation
Analytical simulation modeling
Proceedings of the 40th Conference on Winter Simulation
A preliminary study of optimal splitting for rare-event simulation
Proceedings of the 40th Conference on Winter Simulation
Simulation modeling for analysis
ACM Transactions on Modeling and Computer Simulation (TOMACS)
G-SSASC: simultaneous simulation of system models with bounded hazard rates
Winter Simulation Conference
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Simulation models are often not used to their full potential in the decision-making process. The default simulation strategy of simple serial replication of fixed length runs means that we often waste time generating information about uninteresting models and we only provide a decision at the very end of our study. New simulation techniques such as simultaneous simulation and time dilation have been developed to produce improved decisions at any time with limited or even reduced demands on analysts. Furthermore, we have the tools to determine whether a study should be terminated early or extended based on the demands of the decision-responsible managers and the time-crunched analysts. By collecting information from multiple models at the same time and using this information to continuously update the allocation of finite computational resources, we are able to more effectively leverage every minute of calendar time toward making the best choice. Strategies and tactics are discussed and highlighted through the implementation and analysis of a job shop model. Target success probabilities are achieved faster while achieving goals in study length flexibility at low cost to analyst time.