Evolutionary multimodal optimization: Difference between revisions

Revision as of 18:02, 13 February 2020

Revision as of 00:34, 20 March 2020

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For a comprehensive treatment of multimodal optimization methods in DE, refer the Ph.D thesis Ronkkonen, J. (2009). ''Continuous Multimodal Global Optimization with Differential Evolution Based Methods''.<ref>Ronkkonen,J., (2009). [https://oa.doria.fi/bitstream/handle/10024/50498/isbn%209789522148520.pdf Continuous Multimodal Global Optimization with Differential Evolution Based Methods] {{Webarchive|url=https://web.archive.org/web/20141225150016/https://oa.doria.fi/bitstream/handle/10024/50498/isbn%209789522148520.pdf |date=2014-12-25 }}</ref>

== Multimodal optimization using FOA==

Forest Optimization Algorithm has been extended to multimodal from using the niching method. The basic Sequential Algorithmic Scheme has been applied to clustering population for dividing it into many sub-population <ref>M. Orujpour, et. al (2019), Multi-modal forest optimization algorithm</ref>.

== References ==

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* C. Stoean, M. Preuss, R. Stoean, D. Dumitrescu (2010) [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5491155 Multimodal Optimization by means of a Topological Species Conservation Algorithm]. In IEEE Transactions on Evolutionary Computation, Vol. 14, Issue 6, pages 842–864, 2010.

* S. Das, S. Maity, B-Y Qu, P. N. Suganthan, "[https://www.sciencedirect.com/science/article/pii/S221065021100023X Real-parameter evolutionary multimodal optimization — A survey of the state-of-the-art]", Vol. 1, No. 2, pp.&nbsp;71–88, Swarm and Evolutionary Computation, June 2011.

* M. Orujpour, M-R. Feizi-Derakhshi, T. Rahkar Farshi (2019) [https://doi.org/10.1007/s00521-019-04113-z], Multi-modal forest optimization algorithm. Neural Computing and Applications]

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