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A New Paradigm for Stochastic Optimization and Parallel Simulation

  • Y. C. Ho
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 73)

Abstract

This paper advocates some mind-set changes concerning the problem of optimization of the performance of general discrete event dynamic systems under uncertainty via simulation. We present arguments and evidence that orders of magnitude improvement in computational efficiency are possible and summarize a set of works by the Harvard DEDS group in this area over the past decade.

Keywords

Discrete Event Stochastic Optimization Hill Climbing Discrete Event System Single Instruction Multiple Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1995

Authors and Affiliations

  • Y. C. Ho
    • 1
  1. 1.Division of Applied SciencesHarvard UniversityCambridgeUSA

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