Polygenic inheritance - A haploid scheme that can outperform diploidy

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Abstract

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.

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN 1998 - 5th International Conference, Proceedings
PublisherSpringer Verlag
Pages178-187
Number of pages10
ISBN (Print)3540650784, 9783540650782
DOIs
Publication statusPublished - 1998
Event5th International Conference on Parallel Problem Solving from Nature, PPSN 1998 - Amsterdam, Netherlands
Duration: 27 Sep 199830 Sep 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1498 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Parallel Problem Solving from Nature, PPSN 1998
Country/TerritoryNetherlands
CityAmsterdam
Period27/09/9830/09/98

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