The MATLAB Genetic Algorithm Toolbox
نویسندگان
چکیده
Genetic algorithms (GAs) are stochastic global search and optimization methods that mimic the metaphor of natural biological evolution [1]. GAs operate on a population of potential solutions applying the principle of survival of the fittest to produce successively better approximations to a solution. At each generation of a GA, a new set of approximations is created by the process of selecting individuals according to their level of fitness in the problem domain and reproducing them using operators borrowed from natural genetics. This process leads to the evolution of populations of individuals that are better suited to their environment than the individuals from which they were created, just as in natural adaptation.
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Acknowledgements The production of this Toolbox was made possible by a UK SERC grant on " Genetic Algorithms in Control Systems Engineering " (GR/J17920). Many thanks are due to Hartmut Pohlheim, a visiting researcher from the Technical University Ilmenau, Germany, for the support for real-valued genetic algorithms and his hard work in coding and revising many of the routines in this Toolbox. T...
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