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Issue title: Special Section: Fuzzy Decision Making and Applications in Knowledge Management
Guest editors: Justin Zhang
Article type: Research Article
Authors: Wang, Pinga | Wang, Jieb; * | Wei, Guiwub
Affiliations: [a] Institute of Technology, Sichuan Normal University, Chengdu, P.R. China | [b] School of Business, Sichuan Normal University, Chengdu, P.R. China
Correspondence: [*] Corresponding author. Jie Wang, School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China. E-mail: [email protected].
Abstract: In this paper, we present 2-tuple linguistic neutrosophic EDAS model based on traditional EDAS (Evaluation based on Distance from Average Solution) model and some fundamental theories of 2-tuple linguistic neutrosophic information. Firstly, we briefly review the definition of 2-tuple linguistic neutrosophic sets (2TLNNSs) and introduce the score function, accuracy function and operational laws of 2TLNNs. Next, to fuse overall 2-tuple linguistic neutrosophic evaluation information, we define some new aggregation operators of 2TLNNs based on Hamacher product and sum to propose 2TLNNHWA and 2TLNNHWG operators. Furthermore, combine traditional EDAS model with 2TLNNs information, the 2-tuple linguistic neutrosophic EDAS model is established and all computing steps are simply depicted. In our presented model; it’s more accuracy and effective for considering the conflicting attributes. Finally, a numerical example for safety assessment of construction project has been given to illustrate this new model and some comparisons between 2TLNNs EDAS model and 2TLNNWA, 2TLNNWG, 2TLNNHWA, 2TLNNHWG aggregation operators are also conducted to further illustrate advantages of the new method.
Keywords: MADM problems, 2-tuple linguistic neutrosophic sets (2TLNSs), EDAS model, 2-tuple linguistic neutrosophic number Hamacher weighted average (2TLNNHWA) operators, 2-tuple linguistic neutrosophic number Hamacher weighted geometric (2TLNNHWG) operators, 2TLNNs EDAS model, construction project
DOI: 10.3233/JIFS-179223
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 1597-1608, 2019
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