Affiliations: [a] School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China | [b] School of Business, Sichuan Normal University, Chengdu, P.R. China | [c] School of Statistics, Southwestern University of Finance and Economics, Chengdu, P.R. China | [d] School of Finance, Southwestern University of Finance and Economics, Chengdu, P.R.China
Correspondence:
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Corresponding author. Yanfeng Guo, School of Finance, Southwestern University of Finance and Economics, Chengdu, 610074, P.R. China E-mail: [email protected].
Abstract: In this paper, we provide the probabilistic linguistic multiple attribute group decision making (PL-MAGDM) with incomplete weight information. In such method, the linguistic information firstly is shifted into probabilistic linguistic information. For obtaining the weight information of the attribute, two optimization models are built on the basis of the basic idea of grey relational analysis (GRA), by which the attribute weights can be obtained. Then, the optimal alternative is obtained through calculating largest relative relational degree from the probabilistic linguistic positive ideal solution (PLPIS) which considers both the largest grey relational coefficient (GRC) from the PLPIS and the smallest GRC form probabilistic linguistic negative ideal solution (PLNIS). Finally, a case study for waste incineration plants location problem is given to demonstrate the advantages of the developed methods.
Keywords: multiple attribute group decision making (MAGDM), probabilistic linguistic term sets (PLTSs), GRA method, incomplete weight information, waste incineration plants
