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In this paper, a comprehensive review of PSO as a well-known population-based optimization technique. The review starts by a brief introduction to the behavior of the PSO, then basic concepts and development of PSO are discussed, it's followed by the discussion of PSO inertia weight and constriction factor as well as issues related to parameter setting, selection and tuning, dynamic environments, and hybridization. Also, we introduced the other representation, convergence properties and the applications of PSO. Finally, conclusions and discussion are presented. Limitations to be addressed and the directions of research in the future are identified, and an extensive bibliography is also included.<\/jats:p>","DOI":"10.4018\/ijrsda.2018040101","type":"journal-article","created":{"date-parts":[[2018,1,11]],"date-time":"2018-01-11T21:15:16Z","timestamp":1515705316000},"page":"1-24","source":"Crossref","is-referenced-by-count":64,"title":["Particle Swarm Optimization from Theory to Applications"],"prefix":"10.4018","volume":"5","author":[{"given":"M.A.","family":"El-Shorbagy","sequence":"first","affiliation":[{"name":"Department of Basic Engineering Science, Faculty of Engineering, Menoufia University, Shebin El-Kom, Egypt"}]},{"given":"Aboul Ella","family":"Hassanien","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Computers and Information, Cairo University, Giza,  Egypt"}]}],"member":"2432","reference":[{"key":"IJRSDA.2018040101-0","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2010.08.030"},{"key":"IJRSDA.2018040101-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.chaos.2007.09.063"},{"key":"IJRSDA.2018040101-2","doi-asserted-by":"crossref","unstructured":"Ali A.F., Tawhid M.A. (2016). 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