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One of the main disadvantages of these approaches is the risk of converging to \u201csuboptimal\u201d solutions. In this article, the use of a novel type of genetic algorithm is proposed to overcome this drawback. This approach exploits a fuzzy inference system that controls the search strategies of genetic algorithm on the basis of the real-time status of the optimization process. In this article, this method is tested on classical optimization problems and on three industrial applications that put into evidence the improvement of the capability of avoiding the local minima and the acceleration of the search process.<\/jats:p>","DOI":"10.1515\/jisys-2016-0343","type":"journal-article","created":{"date-parts":[[2018,2,28]],"date-time":"2018-02-28T17:17:12Z","timestamp":1519838232000},"page":"409-422","source":"Crossref","is-referenced-by-count":9,"title":["Fuzzy Adaptive Genetic Algorithm for Improving the Solution of Industrial Optimization Problems"],"prefix":"10.1515","volume":"29","author":[{"given":"Marco","family":"Vannucci","sequence":"first","affiliation":[{"name":"Scuola Superiore Sant\u2019Anna, TeCIP Institute, via Giuseppe Moruzzi, 1 , 56127 Pisa , Italy"}]},{"given":"Valentina","family":"Colla","sequence":"additional","affiliation":[{"name":"Scuola Superiore Sant\u2019Anna, TeCIP Institute, via Giuseppe Moruzzi, 1 , 56127 Pisa , Italy"}]},{"given":"Stefano","family":"Dettori","sequence":"additional","affiliation":[{"name":"Scuola Superiore Sant\u2019Anna, TeCIP Institute, via Giuseppe Moruzzi, 1 , 56127 Pisa , Italy"}]},{"given":"Vincenzo","family":"Iannino","sequence":"additional","affiliation":[{"name":"Scuola Superiore Sant\u2019Anna, TeCIP Institute, via Giuseppe Moruzzi, 1 , 56127 Pisa , Italy"}]}],"member":"374","published-online":{"date-parts":[[2018,2,26]]},"reference":[{"key":"2025120523304241981_j_jisys-2016-0343_ref_001","doi-asserted-by":"crossref","unstructured":"T. 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