@misc{Stańczak_Jarosław_Biologically_2001,
 author={Stańczak, Jarosław},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2001},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={In this paper two new methods of an evolutionary algorithm control are proposed. Methods applied in the evolutionary algorithms are usually derived from nature and prefer solutions where the main role plays randomness, competition and fight among individuals. In the case of evolutionary algorithms, where populations of individuals are usually small it causes a premature convergence to local minima. To avoid this drawback we propose to apply an approach based rather on an agricultural technique. The correctness of such assumption follows from the observation that by operating on small populations of plants or animals it was possible to cultivate species of desired features without randomness, fight and competition. Two new methods of object selections are proposed: a histogram selection and a mixed selection. Also advantages of passing them into the evolutionary algorithm are shown, using examples based on scheduling and TSP.},
 title={Biologically inspired methods of an evolutionary algorithm control},
 type={Text},
 URL={http://www.rcin.org.pl/Content/102575/PDF/RB-2001-22.pdf},
 keywords={Genetic algorithms, Algorytmy genetyczne, Adaptation, Adaptive evolutionary algorithms, Adaptacyjne algorytmy ewolucyjne, Adaptacja},
}