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Adaptive clustering algorithm for recycling cell formation: An Application of fuzzy ART neural networks
Authors:Kwang-Kyu?Seo  author-information"  >  author-information__contact u-icon-before"  >  mailto:kwangkyu@smu.ac.kr"   title="  kwangkyu@smu.ac.kr"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Ji-Hyung?Park
Affiliation:(1) Department of Industrial Information and Systems Engineering, Sangmyng University, San 98-20, Anso-Dong, Chonan, 330-720 Chungnam, Korea;(2) CAD/CAM Research Center, Korea Institute of Science and Technology, Cheongryang, P.O.Box 131, Seoul, Korea
Abstract:The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end-of-life phase. Disposal products have the uncertainties of product status by usage influences during product use phase, and recycling cells are formed design, process and usage attributes. In order to deal with the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. Fuzzy C-mean algorithm and a heuristic approach based on fuzzyART neural network is suggested. Especially, the modified FuzzyART neural network is shown that it has a good clustering results and gives an extension for systematically generating alternative solutions in the recycling cell formation problem. Disposal refrigerators are shown as examples.
Keywords:Fuzzy Theory  Fuzzy C-Mean Algorithm  Fuzzy ART neural network  Recycling Cell Formation
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