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Article type: Research Article
Authors: Yong, Ruia; b; * | Zhu, Aqina | Ye, Juna
Affiliations: [a] Key Laboratory of Rock Mechanics and Geohazards of Zhejiang Province, Shaoxing University, Shaoxing, People’s Republic of China | [b] Civil Engineering Faculty, Shaoxing University, Shaoxing, People’s Republic of China
Correspondence: [*] Corresponding author. Rui Yong, Shaoxing University, Shaoxing 312000, People’s Republic of China. E-mail: yongrui_usx@hotmail.com.
Abstract: A cubic hesitant fuzzy set is a hybrid set which can express uncertain and hesitancy fuzzy information simultaneously. For multiple attribute decision-making problems in engineering practice, the complicated decision information is generally incomplete and indeterminate. Cubic hesitant fuzzy set can be a valuable tool for describing uncertain and hesitancy fuzzy information in uncertain decision environment. Nevertheless, no similarity measure has been used to solve decision-making problems under cubic hesitant environment in previous studies. This paper presents a Jaccard similarity measure between cubic hesitant fuzzy sets and investigates their properties. Then a multiple attribute decision-making method is developed based on the weighted Jaccard similarity measure under cubic hesitant environment. Using this method, the similarity measure values between the ideal alternative and each evaluated alternative are determined to obtain the ranking order of similarity measure values and the best alternative. An illustrative example of the selection problem of project alternatives is utilized to illustrate the application of the developed decision-making method. Finally, the validity of the proposed decision-making method was demonstrated based on the comparison of the decision-making results of the illustrative example with two distance-based similarity measures.
Keywords: Cubic hesitant fuzzy set, multiple attribute decision-making, similarity measure, Jaccard measure
DOI: 10.3233/JIFS-182555
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1075-1083, 2019
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