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Package org.dgpf.search.algorithms.ga.selection

Here you can find all the information about the org.dgpf.search.algorithms.ga.selection package. You may explore the package using the directory listing below. This listing contains all the files contained directly in this package and all its sub-packages. There you can either download a file directly (by clicking on the "download"-link) or read it online (by clicking on its direct link left in the directoy listing. Further information about the package's contents is given at the bottom of this page.

Directory Listing

org.dgpf.search.algorithms.ga.selection
  ├NPGASelection.javadownload download6.648 KB2015-07-22 04:10:59 GMT+0000
  ├OrderedSelection.javadownload download5.318 KB2015-07-22 04:10:59 GMT+0000
  ├package.htmldownload download1.858 KB2015-07-22 04:10:59 GMT+0000
  ├RandomSelection.javadownload download4.038 KB2015-07-22 04:10:59 GMT+0000
  ├RankedSelection.javadownload download3.640 KB2015-07-22 04:10:59 GMT+0000
  ├RouletteWheelSelection.javadownload download3.726 KB2015-07-22 04:10:59 GMT+0000
  ├RoundRobinSelection.javadownload download7.635 KB2015-07-22 04:10:59 GMT+0000
  └TournamentSelection.javadownload download4.972 KB2015-07-22 04:10:59 GMT+0000

This package includes the genetic selection algorithms that can be used by the genetic engines.

Package Specification

This package includes the genetic selection algorithms that can be used by the genetic engines. Currently, we support six selection algorithms:
Tournament Selection
Individuals must compete in a tournament for selection. For each offspring to be produced, a tournament of n randomly chosen individuals will be held, allowing only the best to reproduce.
Ranked Selection
The probability of an individual to be selected is proportional to its rank in the popultion.
Ordered Selection
The probability of an individual to be selected is proportional to its rank divided by the population size and the result raised to a specified power.
Round Robin Selection
This meta-selection algorithm schedules the other in a round robin-like manner and then deferes selection to them. This way, we can easily ensure that we benefit of all the advantages of all selection algorithms.
Round Wheel Selection
The well known round wheel selection algorithm where the probability for an individual of beeing selected is proportional to its fitness.
NPGA Selection
The nieched pareto genetic algorithm for multiobjective optimization, as introduced in J. Horn, N. Nfpliotis, and D.E. Goldberg: "A nieched pareto genetic algorithm for multiobjective optimization", in Proceedings of the First IEEE Conference on Evolutionary Compuation, IEEE World Congress on Computational Intelligence, vol. 1, pp 82-87, Piscataway, New Jersey, IEEE Service Centre, June 1994

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http://dgpf.sourceforge.net/scripts/source/source.php last modified at 2015-07-22 04:10:53 GMT+0000 served at 2017-02-24 01:24:16 GMT+0000.