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Evolutionary optimization within an intelligent hybrid system for design integration

Published online by Cambridge University Press:  01 November 1999

D. SU  and
M. WAKELAM
D. SU
Affiliation:
Department of Mechanical and Manufacturing Engineering, The Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, U.K.
M. WAKELAM
Affiliation:
Department of Mechanical and Manufacturing Engineering, The Nottingham Trent University, Burton Street, Nottingham, NG1 4BU, U.K.
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Abstract

An intelligent hybrid approach has been developed to integrate various stages in total design, including formulation of product design specifications, conceptual design, detail design, and manufacture. The integration is achieved by blending multiple artificial intelligence (AI) techniques and CAD/CAE/CAM into a single environment. It has been applied into power transmission system design. In addition to knowledge-based systems and artificial neural networks, another AI technique, genetic algorithms (GAs), are involved in the approach. The GA is used to conduct optimization tasks: (1) searching the best combination of design parameters to obtain optimum design of gears, and (2) optimization of the architecture of the artificial neural networks used in the hybrid system. In this paper, after a brief overview of the intelligent hybrid system, the GA applications are described in detail.

Keywords

Evolutionary OptimizationArtificial IntelligenceHybrid SystemDesign IntegrationPower Transmission Systems
Type
SPECIAL SECTION ARTICLES
Information
AI EDAM , Volume 13 , Issue 5 , November 1999 , pp. 351 - 363
Copyright
© 1999 Cambridge University Press

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