List of genetic algorithm applications: Difference between revisions

Revision as of 07:00, 19 July 2012

Revision as of 07:49, 21 September 2012

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* Multiple population [[topologies]] and interchange [[methodologies]].

* [[Mutation testing]]

* [[Neural Networksnetwork|Neural Network]]s; particularly [[recurrent neural networks]]<ref>[http://arimaa.com/arimaa/about/Thesis/ Applying Genetic Algorithms to Recurrent Neural Networks for Learning Network Parameters and Architecture]</ref>

* [[Operon]] prediction.<ref name="Wang">{{cite journal|author= Wang S, Wang Y, Du W, Sun F, Wang X, Zhou C, Liang Y | title = A multi-approaches-guided genetic algorithm with application to operon prediction | journal = Artificial Intelligence in Medicine | year = 2007 | volume = 41 | pages = 151–159 | pmid = 17869072 | doi = 10.1016/j.artmed.2007.07.010|issue= 2}}</ref>

* Optimisation of data compression systems, for example using [[wavelet]]s.

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* Solving the machine-component grouping problem required for [[cellular manufacturing]] systems.

* Stochastic optimization ([http://www.math.u-bordeaux1.fr/~delmoral/simu-optim.html] links to particle methods in regulation, optimization, and optimal control)

* [[Tactical asset]] [[allocation]] and [[international equity]] strategies.

* Timetabling problems, such as designing a non-conflicting class timetable for a large university.

* Training [[artificial neural networks]] when pre-classified training examples are not readily obtainable ([[neuroevolution]]).