Evolutionary multimodal optimization: Difference between revisions

Revision as of 11:50, 8 December 2015

Revision as of 04:27, 9 December 2015

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In [[applied mathematics]], '''multimodal optimization''' deals with [[Mathematical optimization|optimization]] tasks that involve finding all or most of the multiple (at least locally optimal) solutions of a problem, as opposed to a single best solution.

Evolutionary multimodal optimization is a branch of [[Evolutionary computation]], which is closely related to [[Machine learning]]. Wong provides a short survey,<ref>Wong, K. C. (2015), [http://arxiv.org/abs/1508.00457 Evolutionary Multimodal Optimization: A Short Survey] arXiv preprint arXiv:1508.00457</ref>, the book of Preuss<ref>Preuss, Mike (2015), [http://www.springer.com/de/book/9783319074061 Multimodal Optimization by Means of Evolutionary Algorithms]</ref> covers the topic in more detail.

== Motivation ==