Improved decision processes through simultaneous simulation and time dilation

  • Authors:
  • Paul Hyden;Lee Schruben

  • Affiliations:
  • Cornell University, Ithaca, NY;University of California at Berkeley, Berkeley, CA

  • Venue:
  • Proceedings of the 32nd conference on Winter simulation
  • Year:
  • 2000

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Abstract

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.