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The approach uses self-organizing map (SOM) neural networks to detect clusters in GA population. After clustering all population and recognizing the number of niches, the phenotypic space is partitioned. Within each partition, a simple GA is independently running to evolve to the actual optima. Before the SOM starts, we allow GA to run several generations until the borders of clusters are identified. Our proposed algorithm is easy to implement, and does not require any prior knowledge about the fitness function. The algorithm was tested for seven multimodal functions and four constrained engineering optimization functions, and the results have been compared with the other related algorithms based on three performance criteria. We found that the present algorithm has acceptable diversification and function evaluation number.<\/jats:p>","DOI":"10.3233\/jifs-131344","type":"journal-article","created":{"date-parts":[[2018,9,14]],"date-time":"2018-09-14T12:30:03Z","timestamp":1536928203000},"page":"4543-4556","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["A genetic algorithm with SOM neural network clustering for multimodal function optimization"],"prefix":"10.1177","volume":"35","author":[{"given":"Atabak Mashhadi","family":"Kashtiban","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran"}]},{"given":"Sohrab","family":"Khanmohammadi","sequence":"additional","affiliation":[{"name":"Department of Control Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran"}]}],"member":"179","published-online":{"date-parts":[[2018,9,11]]},"reference":[{"key":"e_1_3_1_2_2","volume-title":"Department of Civil and Environmental Engineering","author":"Belegundu A.D.","year":"1982","unstructured":"A.D.Belegundu, A study of mathematical programming methods for structural optimization, Ph.D. thesis, Department of Civil and Environmental Engineering, University of Iowa, USA, 1982."},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2012.11.013"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2012.06.014"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.envsoft.2012.04.002"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.07.006"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/9780470544785"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2012.12.020"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2012.04.013"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2011.11.035"},{"issue":"2","key":"e_1_3_1_11_2","first-page":"97","article-title":"Non-convex mixed-integer nonlinear programming: A survey","volume":"17","author":"Burer S.","year":"2012","unstructured":"S.Burer and A.N.Letchford, Non-convex mixed-integer nonlinear programming: A survey, Surv Oper Res Manage Sci 17(2) (2012), 97\u2013106.","journal-title":"Surv Oper Res Manage Sci"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/0045-7949(91)90402-8"},{"key":"e_1_3_1_13_2","first-page":"1","article-title":"Analysis of the publications on the applications of particle swarm optimization","volume":"10","author":"Poli R.","year":"2008","unstructured":"R.Poli, Analysis of the publications on the applications of particle swarm optimization, JAEA 10 (2008), 1\u201310.","journal-title":"JAEA"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1108\/02644401011008577"},{"key":"e_1_3_1_15_2","article-title":"Structural Optimization using Simulated Annealing","author":"Sonmez F.O.","year":"2008","unstructured":"F.O.Sonmez, Structural Optimization using Simulated Annealing, InTech, 2008.","journal-title":"InTech"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2010.09.003"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2004.09.007"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2012.12.004"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00707-009-0270-4"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.02.011"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2009.2017517"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-1539-5_4"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1162\/106365603322519297"},{"key":"e_1_3_1_24_2","volume-title":"ILLiGAL Technical Report No. 97007, Illinois Genetic Algorithms Laboratory","author":"Goldberg D.E.","year":"1997","unstructured":"D.E.Goldberg and L.Wang, Adaptive niching via coevo-lutionary sharing, ILLiGAL Technical Report No. 97007, Illinois Genetic Algorithms Laboratory, University of Illi-noise, Urbana, IL, 1997."},{"key":"e_1_3_1_25_2","first-page":"1633","article-title":"Multinational evolutionary algorithms","author":"Ursem R.K.","year":"1999","unstructured":"R.K.Ursem, Multinational evolutionary algorithms, Proceedings of the IEEE Int. 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