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Rapid Close-to-Optimum Optimization by Genetic Algorithms

Author

Listed:
  • R. Hackl

    (Institut für Physik II, Universität Regensburg, Universitätsstraβe 31, 93053 Regensburg, Germany)

  • I. Morgenstern

    (Institut für Physik II, Universität Regensburg, Universitätsstraβe 31, 93053 Regensburg, Germany)

Abstract

In this article we consider the optimization of np-complete problems with a genetic algorithm. For "real word" problems we regard it to be sufficient to get close to the optimal solution without any guarantee of ever hitting it. Our algorithm was tested on two problem classes: the traveling salesman problem and the product ordering problem; the first is a standard problem, the latter a problem we were confronted with in a practical application. For all investigated problem instances we found very good solutions(

Suggested Citation

  • R. Hackl & I. Morgenstern, 1997. "Rapid Close-to-Optimum Optimization by Genetic Algorithms," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 8(05), pages 1103-1117.
    • Handle: RePEc:wsi:ijmpcx:v:08:y:1997:i:05:n:s0129183197000977
    DOI: 10.1142/S0129183197000977
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