%0 Journal Article %1 Hedberg:2005:IS %A Hedberg, Sara Resse %D 2005 %J Intelligent Systems %K algorithms, biological breeding, computing electronic evolution, evolutionary genetic programming, %N 6 %P 12--15 %R 10.1109/MIS.2005.104 %T Evolutionary computing: the rise of electronic breeding %V 20 %X GAs and their relations, which fall under the umbrella term evolutionary computing, are being harnessed to optimise designs of all sorts. GAs mimics the mechanisms of biological evolution. Populations of individuals evolve by means of reproduction, inheritance, mutation, natural selection, and recombination or crossover (two organisms swap a portion of their genetic code). The result is computational methods that build a population of individuals or designs based on a set of criteria and constraints.

@article{Hedberg:2005:IS, abstract = {GAs and their relations, which fall under the umbrella term evolutionary computing, are being harnessed to optimise designs of all sorts. GAs mimics the mechanisms of biological evolution. Populations of individuals evolve by means of reproduction, inheritance, mutation, natural selection, and recombination or crossover (two organisms swap a portion of their genetic code). The result is computational methods that build a population of individuals or designs based on a set of criteria and constraints.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Hedberg, Sara Resse}, biburl = {https://www.bibsonomy.org/bibtex/2c95382a9070ccc808e76c77dc49843ae/brazovayeye}, doi = {10.1109/MIS.2005.104}, interhash = {ea26c71e330573d9c62fb2082a64097d}, intrahash = {c95382a9070ccc808e76c77dc49843ae}, issn = {1541-1672}, journal = {Intelligent Systems}, keywords = {algorithms, biological breeding, computing electronic evolution, evolutionary genetic programming,}, month = {November-December}, notes = {high level}, number = 6, pages = {12--15}, size = {4 pages}, timestamp = {2008-06-19T17:41:15.000+0200}, title = {Evolutionary computing: the rise of electronic breeding}, volume = 20, year = 2005 }