A PROMETHEE II Approach Based on Probabilistic Hesitant Fuzzy Linguistic Information with Applications to Multi-Criteria Group Decision-Making (ICSSE 2020)
Autor: | Haiyan Xu, Ginger Y. Ke, Lu Chen |
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Rok vydání: | 2021 |
Předmět: |
business.industry
Computer science Probabilistic logic Computational intelligence 02 engineering and technology Machine learning computer.software_genre Theoretical Computer Science Group decision-making Term (time) Hausdorff distance Software Computational Theory and Mathematics Ranking Rule-based machine translation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business computer |
Zdroj: | International Journal of Fuzzy Systems. 23:1556-1580 |
ISSN: | 2199-3211 1562-2479 |
DOI: | 10.1007/s40815-021-01098-7 |
Popis: | Multi-criteria group decision-making (MCGDM) problems are very common in the real world. The complexity of the problem necessitates a solution method that is more in line with the decision-making habits of decision-makers (DMs). This paper introduces a novel type of integrated linguistic information, namely, the Probabilistic Hesitant Fuzzy Linguistic Sets (PHFLSs), which combines the concepts of Hesitant Fuzzy Linguistic Sets and Probabilistic Linguistic Term Sets for solving MCGDM problems. By integrating PHFLSs into the Preference Ranking Organization Method for Enrichment Evaluations II (PROMETHEE II), a group decision-making framework is constructed to effectively generate the best decision given various evaluations from multiple DMs. More specifically, the DMs’ assessments are first developed and normalized based on PHFLSs definitions. Then the Hausdorff distance is employed to compute the distances between different PHFLSs, from which the weights of criteria are derived and then fed into PROMETHEE II for the best group decision. To demonstrate the practicality and capability of the proposed decision framework, a case study on seeking the best open-source software project is presented and discussed. |
Databáze: | OpenAIRE |
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