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However, crossover and mutation operator of standard GA cannot be directly usable for generating test, since integer\u2010coded individuals have to be used and these operators produce duplicated genoms on individuals. In this study, a mutation operation is proposed for preventing the duplications on crossovered individuals. The experiments and analysis show that GA with proposed mutation operator is successful as approximately 100%. \u00a9 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 298\u2013305, 2010; Published online in Wiley InterScience (www.interscience.wiley.com<\/jats:ext-link>); DOI 10.1002\/cae.20260<\/jats:p>","DOI":"10.1002\/cae.20260","type":"journal-article","created":{"date-parts":[[2009,1,20]],"date-time":"2009-01-20T21:11:34Z","timestamp":1232485894000},"page":"298-305","source":"Crossref","is-referenced-by-count":14,"title":["A genetic algorithm for generating test from a question bank"],"prefix":"10.1002","volume":"18","author":[{"given":"Mehmet","family":"Yildirim","sequence":"first","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2010,4,16]]},"reference":[{"key":"e_1_2_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0360-1315(99)00037-8"},{"key":"e_1_2_1_3_2","unstructured":"T.Fei W. J.Hag K. C.Toh andT.Qi Question classification for e\u2010learning by artificial neural network. 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