List of genetic algorithm applications: Difference between revisions

Revision as of 11:19, 2 February 2024

Revision as of 16:46, 22 June 2024

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* [[Power electronics]] design.<ref>{{Cite journal |url=http://www.cs.sysu.edu.cn/~jzhang/papers/SMCC.pdf |doi=10.1109/TSMCC.2005.855497 |access-date=2010-08-09 |archive-url=https://web.archive.org/web/20110707025618/http://www.cs.sysu.edu.cn/~jzhang/papers/SMCC.pdf |archive-date=2011-07-07 |url-status=dead |title=Pseudocoevolutionary genetic algorithms for power electronic circuits optimization |journal=IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews|volume=36 |issue=4 |pages=590–598 |year=2006 |last1=Jun Zhang |last2=Chung |first2=H.S.H. |last3=Lo |first3=W.L. }}</ref>

* [[Traveling salesman problem]] and its applications<ref name="PCB"/>

* Stopping propagations, i.e. deciding how to cut edges in a graph so that some infectious condition (e.g. a disease, fire, computer virus, etc.) stops its spread. A bi-level genetic algorithm (i.e. a genetic algorithm where the fitness of each individual is calculated by running another genetic algorithm) was used due to the Σ^P₂-completeness of the problem.<ref name="GRR">{{cite journal | last1 = Galiana| first1 = J.| last2 = Rodríguez| first2 = I. | last3 = Rubio| first3 = F. | year = 2023| title = How to stop undesired propagations by using bi-level genetic algorithms. | url = https://doi.org/10.1016/j.asoc.2023.110094 | journal = Applied Soft Computing | volume = 136 | issue = 110094| doi = 10.1016/j.asoc.2023.110094}}</ref>

==Earth Sciences==