TESTING STRATEGIES FOR SIMULATION OPTIMIZATION.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Computer simulation models consisting of systems of differential equations, or other mathematical models, can present special problems to numerical optimization methods. Derivatives are often unavailable, function evaluations can be extremely expensive (e. g. , 1 h on an IBM 3090), and the numerical accuracy of each function value may depend on a complicated chain of calculations and so be impractical to prespecify. This last point makes it difficult to calibrate optimization routines that use finite-difference approximations for gradients. A strategy for comparing optimization techniques for these problems is presented, and several interesting findings for quasi-Newton methods, simplex search, and others are reviewed.

Original languageEnglish (US)
Title of host publicationWinter Simulation Conference Proceedings
PublisherACM
Pages391-401
Number of pages11
ISBN (Print)0911801324, 9780911801323
DOIs
StatePublished - Jan 1 1987

Publication series

NameWinter Simulation Conference Proceedings
ISSN (Print)0275-0708

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety
  • Applied Mathematics

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    Barton, R. R. (1987). TESTING STRATEGIES FOR SIMULATION OPTIMIZATION. In Winter Simulation Conference Proceedings (pp. 391-401). (Winter Simulation Conference Proceedings). ACM. https://doi.org/10.1145/318371.318618