{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:18:23Z","timestamp":1777702703183,"version":"3.51.4"},"reference-count":49,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2018,7,24]],"date-time":"2018-07-24T00:00:00Z","timestamp":1532390400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2019,3,16]]},"abstract":"<jats:p>\u00a0The hesitant fuzzy linguistic term set (HFLTS) is usually used in the uncertain decision situation. In order to solve the problem of multi-criteria decision-making (MCDM) with HFLTS, a new MCDM method based on the cloud model and evidence theory is proposed in this paper. A new envelope, whose representation is a synthetic cloud generated by the multiple linguistic term in the HFLTS, is presented for HFLTS to facilitate the computing processes and take both the randomness and fuzziness of linguistic variables into consideration. As to overcome the drawbacks of tradition aggregation operator, the criteria values in the form of the belief degrees are obtained from the synthetic clouds and aggregated using the evidential reasoning algorithm. An illustrative example, which is given to confirm the feasibility and validity, also shows that with the proposed method more reasonable and accurate ranking results can be obtained. Moreover, the belief degree of each linguistic term as well as the hesitant degree of the assessment can be obtained simultaneously.<\/jats:p>","DOI":"10.3233\/jifs-18051","type":"journal-article","created":{"date-parts":[[2018,7,27]],"date-time":"2018-07-27T19:32:27Z","timestamp":1532719947000},"page":"1797-1808","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["A multi-criteria decision-making method for hesitant fuzzy linguistic term set based on the cloud model and evidence theory"],"prefix":"10.1177","volume":"36","author":[{"given":"Jian","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Computer, Nanjing University of Posts and Telecommunications, Nanjing, China"},{"name":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, 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