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Extended Picture Fuzzy MULTIMOORA Method Based on Prospect Theory for Medical Institution Selection

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Abstract

Picture fuzzy numbers (PFNs) with three degrees of memberships can be used to accurately describe the uncertainty of cognitive information. However, picture fuzzy multi-criteria decision-making (MCDM) methods need to be further studied. This paper describes an extended picture fuzzy multi-objective optimization by ratio analysis and a full multiplicative form (MULTIMOORA) method based on the prospect theory (PT) to handle MCDM. By adopting this process, decision-makers (DMs) can provide fuzzy linguistic terms to evaluate relevant criteria. The evaluation information can be transformed into PFNs based on transformation scales. Then, the corresponding weights of criteria can be calculated according to picture fuzzy entropy. Moreover, the PT, which is considered an important tool for describing the psychological cognition of DMs, can be used to obtain a prospect decision matrix. Here, the MULTIMOORA method, which involves the simultaneous application of the picture fuzzy ratio system, the picture fuzzy reference point, and the picture fuzzy multiplicative form methods, was utilized to determine the final rankings of candidate alternatives. We hence propose an extended picture fuzzy MULTIMOORA method based on the PT, the MULTIMOORA method, and picture fuzzy Dice distance measures, which can be applied to MCDM problems where weight information is completely unknown. The feasibility and validity of the proposed method were verified by applying it to medical institution selection. Sensitivity and comparative analyses demonstrated the superiority of this method compared to the existing ones.

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Funding

This work is supported by the Philosophy and Social Science Program in Zhejiang Province, China (No. 21NDJC099YB), the Natural Science Foundation of Zhejiang Province, China (No. LY20G010006), Open Research Projects of Zhejiang Lab (No. 2021KG0AB04), and the National Natural Science Foundation of China (Grant Nos. 71701065, 72171208, and 71771195).

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Authors and Affiliations

  1. School of Information, Zhejiang University of Finance & Economics, Hangzhou, 310018, China

    Chao Tian, Juan-juan Peng & Qing-qi Long

  2. School of Business, Central South University, Changsha, 410083, China

    Jian-qiang Wang

  3. NUS Business School &, The Logistics Institute-Asia Pacific, National University of Singapore, Singapore, Singapore

    Mark Goh

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  1. Chao Tian
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  2. Juan-juan Peng
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Correspondence to Juan-juan Peng.

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Tian, C., Peng, Jj., Long, Qq. et al. Extended Picture Fuzzy MULTIMOORA Method Based on Prospect Theory for Medical Institution Selection. Cogn Comput 14, 1446–1463 (2022). https://doi.org/10.1007/s12559-022-10006-6

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