Probabilistic Linguistic Analytic Hierarchy Process and Its Application on the Performance Assessment of Xiongan New Area

Wanying Xie (), Zeshui Xu, Zhiliang Ren () and Hai Wang ()
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Wanying Xie: School of Economics and Management, Southeast University, Nanjing 211189, P. R. China
Zeshui Xu: School of Economics and Management, Southeast University, Nanjing 211189, P. R. China2Business School, Sichuan University, Chengdu 610064, P. R. China
Zhiliang Ren: School of Economics and Management, Southeast University, Nanjing 211189, P. R. China
Hai Wang: School of Economics and Management, Southeast University, Nanjing 211189, P. R. China

International Journal of Information Technology & Decision Making (IJITDM), 2018, vol. 17, issue 06, 1693-1724

Abstract: Analytic Hierarchy Process (AHP) is one of the most favorable decision tools for dealing with complex decision-making problems. Probabilistic linguistic term set (PLTS) is an up-to-date tool to deal with uncertain information in the decision-making process. In this paper, we extend the AHP to the probabilistic linguistic environment for perfecting the modeling ability of AHP in various decision-making problems. In order to apply the PLTSs to the AHP properly, we first redefine the probabilistic linguistic comparison matrix (PLCM) and propose a new consistency index. Then, we propose a new approach to check and improve the consistency of the PLCMs. After that, we aggregate the individual PLCMs into the collective PLCM and derive the priorities of the collective PLCM. Finally, we combine the priorities with the decision matrix to complete the ranking of alternatives, and a case concerning the performance assessments of three new areas is given and the comparative analysis about the results is performed to demonstrate the feasibility of the proposed method.

Keywords: Probabilistic linguistic terms set; probabilistic linguistic comparison matrix; possibility degree; probabilistic linguistic analytic hierarchy process; multi-criteria group decision-making (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0219622017500420

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