Author
Qi Pang
Bio: Qi Pang is an academic researcher from Sichuan University. The author has contributed to research in topics: Probabilistic relevance model & Group decision-making. The author has an hindex of 1, co-authored 1 publications receiving 520 citations.
Papers
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TL;DR: An extended TOPSIS method and an aggregation-based method respectively for multi-attribute group decision making (MAGDM) with probabilistic linguistic information, and apply them to a practical case concerning strategy initiatives.
807 citations
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TL;DR: A LGDM consensus model in which the clusters are allowed to change and the decision makers provide preferences using fuzzy preference relations is proposed, and an emergency decision to choose a rescue plan is illustrated to validate the proposed method and demonstrate distinctive characteristics compared with the existing approaches.
278 citations
TL;DR: This paper redefine some more logical operational laws for linguistic terms, hesitant fuzzy linguistic elements (HFLEs) and probabilistic linguistic term sets (PLTSs) based on two equivalent transformation functions to keep the operation results more reasonable in decision making with linguistic information.
274 citations
TL;DR: A strongly robust method to solve multiexperts multicriteria decision making problems with linguistic evaluations, MULTIMOORA, is proposed by integrating the subjective opinions with the correlation coefficients between criteria and enhanced by the improved Borda rule.
Abstract: The probabilistic linguistic term set (PLTS) is a powerful technique in representing linguistic evaluations of individuals or groups in the process of decision making. The aim of this paper is to propose a strongly robust method to solve multiexperts multicriteria decision making problems with linguistic evaluations. To enrich the computation and to improve the measures of PLTS, we first define an expectation function of it. In addition, we advance three kinds of probabilistic linguistic distance measures reflecting on the difference of linguistic terms and probabilities at the same time to make up for the defects of the existing distance measures, and then propose the similarity and correlation measures. Integrating the subjective opinions with the correlation coefficients between criteria, we put forward a combined weight determining method. The robustness of the ranking method, MULTIMOORA, is enhanced by the improved Borda rule. Based on these research findings, a probabilistic linguistic MULTIMOORA method is proposed. Finally, the developed method is applied to an empirical example concerning the selection of shared karaoke television brands. The effectiveness of the proposed method is verified by some comparative analyses.
262 citations
TL;DR: A comprehensive Multiple Criteria Group Decision Making (MCGDM) method with probabilistic linguistic information based on a new consensus measure and a novel outranking method, Gained and Lost Dominance Score (GLDS), validated by a case study of selecting optimal green enterprises.
247 citations
TL;DR: The DHHFL-MULTIMOORA method is applied to deal with a practical case about selecting the optimal city in China by evaluating the implementation status of haze controlling measures and some comparisons are provided to show the advantages of the proposed method.
247 citations