Population variation in genetic programming
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gp-bibliography.bib Revision:1.8098
- @Article{Kouchakpour:2007:IS,
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author = "Peyman Kouchakpour and Anthony Zaknich and
Thomas Braunl",
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title = "Population variation in genetic programming",
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journal = "Information Sciences",
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year = "2007",
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volume = "177",
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number = "17",
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pages = "3438--3452",
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month = "1 " # sep,
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keywords = "genetic algorithms, genetic programming, Computational
effort, Average number of evaluations, Convergence,
Population variation",
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DOI = "doi:10.1016/j.ins.2007.02.032",
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abstract = "A new population variation approach is proposed,
whereby the size of the population is systematically
varied during the execution of the genetic programming
process with the aim of reducing the computational
effort compared with standard genetic programming
(SGP). Various schemes for altering population size
under this proposal are investigated using a
comprehensive range of standard problems to determine
whether the nature of the population variation, i.e.
the way the population is varied during the search, has
any significant impact on GP performance. The initial
population size is varied in relation to the initial
population size of the SGP such that the worst case
computational effort is never greater than that of the
SGP. It is subsequently shown that the proposed
population variation schemes do have the capacity to
provide solutions at a lower computational cost
compared with the SGP.",
- }
Genetic Programming entries for
Peyman Kouchakpour
Anthony Zaknich
Thomas Braunl
Citations