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Anticipatory Versus Traditional Genetic Algorithm

Author

Listed:
  • Irina Mocanu

    (University Politehnica of Bucharest, Computer Science and Engineering Dept., Splaiul Independentei 313, sector 6, 060042, Bucharest, Romania)

  • Eugenia Kalisz

    (University Politehnica of Bucharest, Computer Science and Engineering Dept., Splaiul Independentei 313, sector 6, 060042, Bucharest, Romania)

Abstract

This paper evaluates the performances of a new type of genetic algorithms - anticipatory genetic algorithms (AGA) versus traditional genetic algorithms (GA). The performances are evaluated based on two simple problems using different genetic operators. The evaluation included in the paper shows that AGA is superior to traditional genetic algorithm from both speed and accuracy points of view. Then we evaluate the two types of genetic algorithms for solving the problem of image annotation, which will be used in content based image retrieval systems. In this case the AGA performances are superior to GA, too.

Suggested Citation

  • Irina Mocanu & Eugenia Kalisz, 2012. "Anticipatory Versus Traditional Genetic Algorithm," Romanian Economic Business Review, Romanian-American University, vol. 6(2), pages 278-290, December.
    • Handle: RePEc:rau:journl:v:6:y:2012:i:2:p:278-290
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    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/WI12/JISOM-WI12-A5.pdf
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