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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Veröffentlicht in:Naval research logistics 1995-12, Vol.42 (8), p.1203-1232
Hauptverfasser: Crouch, Ingrid W. M., Greenwood, Allen G., Rees, Loren Paul
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container_title Naval research logistics
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creator Crouch, Ingrid W. M.
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description 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.
doi_str_mv 10.1002/1520-6750(199512)42:8<1203::AID-NAV3220420807>3.0.CO;2-8
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source Wiley Online Library Journals Frontfile Complete
subjects Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Problem solving, game playing
Simulation
Software
title Use of a classifier in a knowledge-based simulation optimization system
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