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Wyszukujesz frazę "Multiple Attribute Decision Making (MADM)" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Dual hesitant Pythagorean fuzzy Bonferroni mean operators in multi-attribute decision making
Autorzy:
Tang, Xiyue
Wei, Guiwu
Powiązania:
https://bibliotekanauki.pl/articles/229277.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
multiple attribute decision making
MADM
dual hesitant Pythagorean fuzzy sets
dual hesitant Pythagorean fuzzy Bonferroni mean operator
DHPFBM
dual hesitant Pythagorean fuzzy geometric Bonferroni mean operator
DHPFGBM
supplier selection
supply chain management
Opis:
In this paper, we investigate the multiple attribute decision making problems based on the Bonferroni mean operators with dual Pythagorean hesitant fuzzy information. Firstly, we introduce the concept and basic operations of the dual hesitant Pythagorean fuzzy sets, which is a new extension of Pythagorean fuzzy sets. Then, motivated by the idea of Bonferroni mean operators, we have developed some Bonferroni mean aggregation operators for aggregating dual hesitant Pythagorean fuzzy information. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the dual hesitant Pythagorean fuzzy multiple attribute decision making problems. Finally, a practical example for supplier selection in supply chain management is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Źródło:
Archives of Control Sciences; 2019, 29, 2; 339-386
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dual hesitant pythagorean fuzzy Hamacher aggregation operators in multiple attribute decision making
Autorzy:
Wei, G.
Lu, M.
Powiązania:
https://bibliotekanauki.pl/articles/229895.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
multiple attribute decision making (MADM)
dual Pythagorean hesitant fuzzy values
dual hesitant Pythagorean fuzzy Hamacher hybrid average (DHPFHHA) operator
dual hesitant Pythagorean fuzzy Hamacher hybrid geometric (DHPFHHG) operator
power aggregation operators
Opis:
In this paper, we investigate the multiple attribute decision making (MADM) problem based on the Hamacher aggregation operators with dual Pythagorean hesitant fuzzy information. Then, motivated by the ideal of Hamacher operation, we have developed some Hamacher aggregation operators for aggregating dual hesitant Pythagorean fuzzy information. The prominent characteristic of these proposed operators are studied. Then, we have utilized these operators to develop some approaches to solve the dual hesitant Pythagorean fuzzy multiple attribute decision making problems. Finally, a practical example for supplier selection in supply chain management is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Źródło:
Archives of Control Sciences; 2017, 27, 3; 365-395
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective data envelopment analysis: A game of multiple attribute decision-making
Autorzy:
Chen, Yuh Wen
Powiązania:
https://bibliotekanauki.pl/articles/522074.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Ekonomiczny w Katowicach
Tematy:
Data Envelopment Analysis (DEA)
Multi-Objective Linear Programming (MOLP)
Multiple Attribute Decision Making (MADM)
Research and Development (R&D) efficiency
Opis:
Aim/purpose ‒ The traditional data envelopment analysis (DEA) is popularly used to evaluate the relative efficiency among public or private firms by maximising each firm’s efficiency: the decision maker only considers one decision-making unit (DMU) at one time; thus, if there are n firms for computing efficiency scores, the resolution of n similar problems is necessary. Therefore, the multi-objective linear programming (MOLP) problem is used to simplify the complexity. Design/methodology/approach ‒ According to the similarity between the DEA and the multiple attribute decision making (MADM), a game of MADM is proposed to solve the DEA problem. Related definitions and proofs are provided to clarify this particular approach. Findings ‒ The multi-objective DEA is validated to be a unique MADM problem in this study: the MADM game for DEA is eventually identical to the weighting multi-objective DEA. This MADM game for DEA is used to rank ten LCD companies in Taiwan for their research and development (R&D) efficiencies to show its practical application. Research implications/limitations ‒ The main advantage of using an MADM game on the weighting multi-objective DEA is that the decision maker does not need to worry how to set these weights among DMUs/objectives, this MADM game will decide the weights among DMUs by the game theory. However, various DEA models are eventually evaluation tools. No one can guarantee us with 100% confidence that their evaluated results of DEA could be the absolute standard. Readers should analyse the results with care. Originality/value/contribution ‒ A unique link between the multi-objective CCR DEA and the MADM game for DEA is established and validated in this study. Previous scholars seldom explored and developed this breathtaking view before.
Źródło:
Journal of Economics and Management; 2019, 37; 156-177
1732-1948
Pojawia się w:
Journal of Economics and Management
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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