Asymmetric normalized probabilistic linguistic term set based on prospect theory and its application to multi-attribute decision-making
The probabilistic linguistic term set (PLTS) shows great superiority in expressing decision-makers’ opinions. The multi-attribute decision-making (MADM) problem under a PLTS environment has gained attention from numerous scholars. However, the majority of current studies are not precise enough in ca...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Jg. 27; H. 15; S. 10427 - 10445 |
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| Sprache: | Englisch |
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01.08.2023
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| ISSN: | 1432-7643, 1433-7479 |
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| Abstract | The probabilistic linguistic term set (PLTS) shows great superiority in expressing decision-makers’ opinions. The multi-attribute decision-making (MADM) problem under a PLTS environment has gained attention from numerous scholars. However, the majority of current studies are not precise enough in capturing information on PLTS. To address this problem, this paper presents a preference ranking organization method for enrichment of evaluations (PROMETHEE) based on the redefined PLTS and novel score function to solve MADM problems under a PLTS environment. First, an asymmetric normalized PLTS based on prospect theory (ANPLTSPT) is developed. Compared with the PLTS, ANPLTSPT offers a more realistic portrayal of decision-makers’ psychological state while ensuring the superiority of the PLTS. Second, regarding the structural complexity of ANPLTSPT, this paper attempts to simplify the computational process through a score function that can embody the characteristics of ANPLTSPT. Inspired by previously formulated score functions, a novel score function called Score-InInHe is developed, the corresponding definitions are given, and some further properties are discussed. With the support of the proposed Score-InInHe, the total score entropy is defined and an objective method to determine the attribute weights is proposed. Finally, the proposed approach is applied to the selection of a green supplier and the determination of air quality. The validity and realistic applicability of the proposed approach are demonstrated through comparative analyses and discussions. |
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| AbstractList | The probabilistic linguistic term set (PLTS) shows great superiority in expressing decision-makers’ opinions. The multi-attribute decision-making (MADM) problem under a PLTS environment has gained attention from numerous scholars. However, the majority of current studies are not precise enough in capturing information on PLTS. To address this problem, this paper presents a preference ranking organization method for enrichment of evaluations (PROMETHEE) based on the redefined PLTS and novel score function to solve MADM problems under a PLTS environment. First, an asymmetric normalized PLTS based on prospect theory (ANPLTSPT) is developed. Compared with the PLTS, ANPLTSPT offers a more realistic portrayal of decision-makers’ psychological state while ensuring the superiority of the PLTS. Second, regarding the structural complexity of ANPLTSPT, this paper attempts to simplify the computational process through a score function that can embody the characteristics of ANPLTSPT. Inspired by previously formulated score functions, a novel score function called Score-InInHe is developed, the corresponding definitions are given, and some further properties are discussed. With the support of the proposed Score-InInHe, the total score entropy is defined and an objective method to determine the attribute weights is proposed. Finally, the proposed approach is applied to the selection of a green supplier and the determination of air quality. The validity and realistic applicability of the proposed approach are demonstrated through comparative analyses and discussions. |
| Author | Li, Meijuan Lu, Jincheng Zhang, Jiarong |
| Author_xml | – sequence: 1 givenname: Jiarong surname: Zhang fullname: Zhang, Jiarong organization: School of Economics and Management, Fuzhou University – sequence: 2 givenname: Meijuan surname: Li fullname: Li, Meijuan email: mjli853@fzu.edu.cn organization: School of Economics and Management, Fuzhou University, Research Center of Fujian Economic High-Quality Development Based on Social Science Planning of Fujian Province in China – sequence: 3 givenname: Jincheng surname: Lu fullname: Lu, Jincheng organization: School of Economics and Management, Fuzhou University |
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