Polygenic inheritance — A haploid scheme that can outperform diploidy

  • Conor Ryan
  • J. J. Collins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1498)


Nonstationary function optimisation has proved a difficult area for Genetic Algorithms. Standard haploid populations find it difficult to track a moving target and tend to converge to a local optimum that appears early in a run. While it is generally accepted that various approaches involving diploidy can cope better with these kinds of problems, none of these have gained wide acceptance in the GA community. We survey a number of diploid GAs and outline some possible reasons why they have failed to gain wide acceptance, before describing a new haploid system which uses Polygenic Inheritance. Polygenic inheritance differs from most implementations of GAs in that several genes contribute to each phenotypic trait. A nonstationary function optmisation problem from the literature is described, and it is shown how various represenation scheme affect the performance of GAs on this problem.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Conor Ryan
    • 1
  • J. J. Collins
    • 1
  1. 1.Dept. of Computer Science and Information SystemsUniversity of LimerickIreland

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