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

Published:01 December 1992Publication History
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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.

References

  1. 1 D.E.Goldberg, Genetic Algorithms, in Search, Optimization & Machine Learning, Addison Wesley, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. 2 E.G. Talbi, P.Bessiere, "A Parallel genetic algorithm for the graph partitioning problem" available as IMAG Report. (Contact bessiere@ima g.fr)Google ScholarGoogle Scholar
  3. 3 J.M.Filloque, E.Gauuin, B.Pottier, Efficient Global Computation on a Processor Network with Programmable Logic, ARLE91, LNCS 505, Springer-Verlag, June 91. Google ScholarGoogle ScholarDigital LibraryDigital Library

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

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                  cover image ACM SIGPLAN OOPS Messenger
                  ACM SIGPLAN OOPS Messenger  Volume 4, Issue 2
                  April 1993
                  284 pages
                  ISSN:1055-6400
                  DOI:10.1145/157710
                  Issue’s Table of Contents
                  • cover image ACM Conferences
                    OOPSLA '92: Addendum to the proceedings on Object-oriented programming systems, languages, and applications (Addendum)
                    December 1992
                    320 pages
                    ISBN:0897916107
                    DOI:10.1145/157709

                  Copyright © 1992 ACM

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                  Association for Computing Machinery

                  New York, NY, United States

                  Publication History

                  • Published: 1 December 1992

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