{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T22:53:40Z","timestamp":1762210420208},"reference-count":33,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Unc. Fuzz. Knowl. Based Syst."],"published-print":{"date-parts":[[2006,6]]},"abstract":"<jats:p> Before implementing a design of a large engineering system different design proposals are evaluated and ranked according to different criteria, such as, safety, cost and technical performance. The experts' knowledge about these criteria is usually vague and\/or incomplete, and their nature may be quantitative or qualitative. Therefore the preference modelling for the criteria could imply the use of different types of information such as numerical and\/or linguistic (non-homogeneous framework). However, in most of evaluation processes the experts are forced to provide their scores in the same expression domain and in the same scale. The aim of this paper is to propose an evaluation model based on a multi-criteria decision analysis that offers to the experts the possibility of expressing their knowledge in a non-homogeneous evaluation framework, such that the experts can provide their assessments within different domains and scales according to their knowledge and the nature of the criteria. To do so, we propose the use of the fuzzy logic and the fuzzy linguistic approach in order to manage the uncertainty related to the information provided by the experts. <\/jats:p>","DOI":"10.1142\/s0218488506004035","type":"journal-article","created":{"date-parts":[[2006,6,19]],"date-time":"2006-06-19T06:53:38Z","timestamp":1150700018000},"page":"317-336","source":"Crossref","is-referenced-by-count":50,"title":["A FUZZY MODEL FOR DESIGN EVALUATION BASED ON MULTIPLE CRITERIA ANALYSIS IN ENGINEERING SYSTEMS"],"prefix":"10.1142","volume":"14","author":[{"given":"LUIS","family":"MARTINEZ","sequence":"first","affiliation":[{"name":"Department of Computer Sciences, University of Ja\u00e9n, 23071 Ja\u00e9n, Spain"}]},{"given":"JUN","family":"LIU","sequence":"additional","affiliation":[{"name":"School of Computing and Mathematics, University of Ulster at Jordanstown, Newtonabbey, Co Antrim, BT37 0QB, N. Ireland, UK"}]},{"given":"JIAN-BO","family":"YANG","sequence":"additional","affiliation":[{"name":"Manchester Business School (East), The University of Manchester, Manchester M15 6PB, UK"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1016\/0377-2217(95)00091-7"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488501000983"},{"key":"rf4","volume-title":"Social Choice and Individual Values","author":"Arrow K. J.","year":"1963"},{"key":"rf5","doi-asserted-by":"publisher","DOI":"10.1109\/91.493906"},{"key":"rf6","unstructured":"P. P.\u00a0Bonissone and K. S.\u00a0Decker, Uncertainty in Artificial Intelligence, eds. L. H.\u00a0Kanal and J. 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