Evolutionary computation: From genetic algorithms to genetic programming
Studies in Computational Intelligence, ISSN: 1860-949X, Vol: 13, Page: 1-20
2006
- 46Citations
- 79Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Review Description
Evolutionary computation, offers practical advantages to the researcher facing dificult optimization problems. These advantages are multi-fold, including the simplicity of the approach, its robust response to changing circumstance, its flexibility, and many other facets. The evolutionary approach can be applied to problems where heuristic solutions are not available or generally lead to unsatisfactory results. As a result, evolutionary computation have received increased interest, particularly with regards to the manner in which they may be applied for practical problem solving. © 2006 Springer-Verlag Berlin Heidelberg.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=33845246610&origin=inward; http://dx.doi.org/10.1007/11521433_1; http://www.springerlink.com/index/10.1007/11521433_1; https://link.springer.com/10.1007/3-540-32498-4_1; http://dx.doi.org/10.1007/3-540-32498-4_1; http://www.springerlink.com/index/10.1007/3-540-32498-4_1; http://www.springerlink.com/index/pdf/10.1007/3-540-32498-4_1; https://dx.doi.org/10.1007/3-540-32498-4_1; https://link.springer.com/chapter/10.1007/3-540-32498-4_1; https://dx.doi.org/10.1007/11521433_1
Springer Nature
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