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Multi-stage multi-attribute decision-making method based on the prospect theory and triangular fuzzy MULTIMOORA

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Abstract

This paper proposed a novel multi-stage multi-attribute decision-making method, in which the period weights and attribute weights are completely unknown, and attribute values are triangular fuzzy numbers. At first, the triangular fuzzy prospect decision matrices of different periods are constructed and the period weights optimization model is built according to the time degree and the prospect value deviation of alternatives in different periods. The attribute weights are obtained by the maximum deviation method. Then, MULTIMOORA is extended into the triangular fuzzy environment. Based on the new form of MULTIMOORA and dominance theory, the final ranking of alternatives can be got. Finally, a numerical example is presented to illustrate the feasibility and effectiveness of the proposed method.

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Acknowledgements

This study was funded by the National Science Foundation (Grant No. 91024029).

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Authors and Affiliations

  1. Faculty of Management and Economics, Dalian University of Technology, Dalian, 116024, China

    Wen-feng Dai & Qiu-yan Zhong

  2. School of Information Engineering, Lanzhou University of Finance and Economics, Lanzhou, 730020, China

    Wen-feng Dai & Chun-ze Qi

Authors
  1. Wen-feng Dai
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  2. Qiu-yan Zhong
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  3. Chun-ze Qi
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Correspondence to Wen-feng Dai.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Dai, Wf., Zhong, Qy. & Qi, Cz. Multi-stage multi-attribute decision-making method based on the prospect theory and triangular fuzzy MULTIMOORA. Soft Comput 24, 9429–9440 (2020). https://doi.org/10.1007/s00500-018-3017-0

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