Use of a classifier in a knowledge-based simulation optimization system

This article defines and develops a simulation optimization system based upon response surface classification and the integration of multiple search strategies. Response surfaces are classified according to characteristics that indicate which search technique will be most successful. Typical surface...

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Bibliographic Details
Published in:Naval research logistics 1995-12, Vol.42 (8), p.1203-1232
Main Authors: Crouch, Ingrid W. M., Greenwood, Allen G., Rees, Loren Paul
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Problem solving, game playing
Simulation
Software
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Summary:This article defines and develops a simulation optimization system based upon response surface classification and the integration of multiple search strategies. Response surfaces are classified according to characteristics that indicate which search technique will be most successful. Typical surface characteristics include statistical measures and topological features, while search techniques encompass response surface methodology, simulated annealing, random search, etc. The classify‐then‐search process flow and a knowledge‐based architecture are developed and then demonstrated with a detailed computer example. The system is useful not only as an approach to optimizing simulations, but also as a means for integrating search techniques and thereby providing the user with the most promising path toward an optimal solution. © 1995 John Wiley & Sons, Inc.
ISSN:0894-069X
1520-6750
DOI:10.1002/1520-6750(199512)42:8<1203::AID-NAV3220420807>3.0.CO;2-8