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The objective of this paper is to evaluate and compare these two tools applied to a flexible manufacturing system performance optimization context, based on simulation. The principal purpose of this comparison is to determine their performances based on the quality of the obtained results and the gain in the simulation effort. The results of the comparison, applied to a flexible manufacturing system mean flow time optimization, show that the Arena\/OptQuest optimization platform outperforms the Taguchi optimization method. Indeed, the Arena\/OptQuest permits one, through the lowest experimental effort, to reliably minimize the mean flow time of the studied flexible manufacturing system more than the Taguchi method.<\/jats:p>","DOI":"10.1177\/0037549718819804","type":"journal-article","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T15:07:45Z","timestamp":1547046465000},"page":"1085-1096","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["Performance optimization of a flexible manufacturing system using simulation: the Taguchi method versus OptQuest"],"prefix":"10.1177","volume":"95","author":[{"given":"Abdessalem","family":"Jerbi","sequence":"first","affiliation":[{"name":"UR \u201cLOgistique, Gestion Industrielle et Qualit\u00e9\u201d (LOGIQ) Universit\u00e9 de Sfax, Institut Sup\u00e9rieur de Gestion Industrielle, 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