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Iranian Journal of Fuzzy Systems، جلد ۱۷، شماره ۶، صفحات ۹۳-۱۰۵
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عنوان انگلیسی Pythagorean interval 2-tuple linguistic VIKOR method for evaluating human factors in construction project management
چکیده انگلیسی مقاله In a construction project, there are many factors that affect the project quality, such as people, materials, machinery, environment, etc. Among them, people have the greatest influence on the project quality, whether people participate directly or indirectly. This paper mainly evaluates human factors in the process of construction project management, such as workers’ proficiency, workers’ safety awareness, technical workers’ quality, and workers’ emergency capacity, with the purpose of helping China’s construction project to proceed smoothly. In this manuscript, a multi-attribute group decision-making (MAGDM) technique based on Pythagorean interval 2-tuple linguistic numbers (PI2TLNs) and VIKOR method is proposed to evaluate human factors in construction projects. PI2TLNs are used to represent performance assessments of decision makers. Relying on Pythagorean interval 2-tuple linguistic weighted averaging (PI2TLWA)/Pythagorean interval 2-tuple linguistic weighted geometric (PI2TLWG) operator, the evaluation information given by experts is fused into a group decision matrix. Combined with the essential VIKOR method, PI2TLN-VIKOR’ framework is established. The effectiveness of this method is verified by an example, and compared with two algorithms and PI2TLN-TODIM method.
کلیدواژه‌های انگلیسی مقاله Multiple attribute group decision making (MAGDM), Pythagorean interval 2-tuple linguistic numbers (PI2TLNs), VIKOR method, construction project management
نویسندگان مقاله G. Wei |
School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China

G. Wei |
School of Business, Sichuan Normal University, Chengdu, 610101, P.R. China

R. Lin |
School of Economics and Management, Chongqing University of Arts and Sciences, Chongqing 402160, China

C. Wei |
School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, P.R. China

C. Wei |
School of Statistics, Southwestern University of Finance and Economics, Chengdu, 611130, P.R. China

S. Dai |
School of Electronics and Information Engineering, Taizhou University, Taizhou 318000, China

نشانی اینترنتی https://ijfs.usb.ac.ir/article_5603_5f538a86e5251f03c1b664777343e551.pdf
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