An object-oriented environment for specification and concurrent execution of genetic algorithms

Authors:
L. Lemarchand;A. Plantec;B. Pottier;S. Zanati
Affiliations:
-;-;-;-
Venue:
OOPSLA '92 Addendum to the proceedings on Object-oriented programming systems, languages, and applications (Addendum)
Year:
1992

Citing 2
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Efficient global computations on a processor network with programmable logic

PARLE '91 Proceedings on Parallel architectures and languages Europe : volume I: parallel architectures and algorithms: volume I: parallel architectures and algorithms
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning

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Abstract

Genetic algorithms (GA) mimic natural reproduction to search for complex problem solutions. Their principles are shortly explained. A point of interest is the regular and repetititve structure of computation involving communication, data exchanges, and control phases. Interaction with presentation and analysis tools is also a requirement. This make sense for the definition of a general framework allowing fast building of parallel applications in an object-oriented system. A GA workbench is developed using the Smalltalk-80 system with parallel machine code generation in mind.