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#:: Elitism mode, available for the Basic GA subtype only, allows the fittest individuals to survive and produce “children” "children" over a span of multiple generations. #: '''Incremental''' subtype does not create an entirely new population for each generation. It simply adds only one or two children to the population each time the next generation is created. These one or two children replace one or two individuals in the previous generation. The individuals to be replaced by the children are chosen according to the Replacement Schemas used.  <br>#: '''Replacement Schemas'''  #: Replacement Schemas are available for Incremental subtype only. Schemas define how a new generation should be integrated into the population. There are three schemes available: '''Worst''', '''Parent''', and '''Random'''. <br>#: '''Worst''' – least fit individuals are replaced <br>#: '''Parent''' – parent individuals are replaced <br>#: '''Random''' – individuals are replaced randomly <br> #: '''Offspring Number'''  #: Offspring Number is the number of children to be added each time that a new generation is created. '''One''' or '''Two''' children can be added. #: * The fitness of each individual is evaluated and the least fit individuals discarded.#: * The process is repeated, until the specified degree of convergence or generation number is reached (depends on GA setting selected). <br>#: '''GA Convergence Type'''  #: Genetic Algorithms optimization process has no implicit final result and thus can proceed forever. Therefore, an "ending-point" must be specified, indicating when the optimization process must come to an end. #: Two GA optimization "ending-point" criteria types can be selected: '''Terminate-Upon-Generation''' and '''Terminate-Upon-Convergence'''. #: '''Terminate-Upon-Generation''' will stop the optimization process once the specified '''Maximum Number of Generations''' is reached. #: '''Terminate-Upon-Convergence''' will stop the optimization process once the defined '''Convergence Rate''' is reached, or once the defined '''Maximum Number of Generations''' is reached.<br> #: GA optimization "ending-point" criterion is selected in the '''Conversion Type''' drop-down list. #: The desired Maximum Number of Generations, Minimum Number of Generations, and Conversion Rate can be set in the corresponding text boxes. <br>#: '''Convergence Rate'''  #: Convergence Rate of generations is the ratio between the Convergence value of the two most recent generations and the Convergence value of the current generation and the generation N generations ago. <br>#: GA calculation is stopped after meeting С [x – N] / C [x] >= P condition where: <br>#: x – ordinal number of the current generation; <br>#: С[x] – convergence value of the two most recent generations; <br>#: N – defined minimal number of the generations; <br>#: P - convergence rate; values used are usually close to 1, with the default value of 0.99. <br>#: <div style="background-color: #E3FBE5;">Note: Convergence Rate is not calculated for generations that have an ordinal number less than the defined minimal number of the generations.</div> <br>#: '''Further Reading''' #: This is only a brief introduction to genetic algorithms. We recommend that you learn more about GA on the Internet, e.g. [[http://en.wikipedia.org/wiki/Genetic_algorithm Wikipedia]]