Unbalanced double hierarchy linguistic group decision-making method based on SWARA and S-ARAS for multiple attribute group decision-making problems

Teng, Fei; Shen, Mengjiao

doi:10.1007/s10462-022-10198-1

Cited by 8 publications

(1 citation statement)

References 44 publications

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“…MAGDM is an important component of the decision-making field, mainly solving limited alternative decision-making problems containing multiple attributes [ [29] , [30] , [31] , [32] , [33] , [34] , [35] ]. Its characteristic is to evaluate a limited number of alternative solutions through a certain method based on the evaluation information provided by the DMs, and then obtain a ranking [ [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] ].…”

Section: Introductionmentioning

confidence: 99%

A novel IFN-CSM-CoCoSo approach for multiple-attribute group decision-making with intuitionistic fuzzy sets: An application in assessing corporate social responsibility performance

Nie

2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

A novel IFN-CSM-CoCoSo approach for multiple-attribute group decision-making with intuitionistic fuzzy sets: An application in assessing corporate social responsibility performance

Nie

2024

Heliyon

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Toward robust decision-making under multiple evaluation scenarios with a novel fuzzy ranking approach: green supplier selection study case

Więckowski,

Wątróbski,

Sałabun

2024

Artif Intell Rev

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In the evolving field of decision-making, the continuous advancement of technologies and methodologies drives the pursuit of more reliable tools. Decision support systems (DSS) provide information to make informed choices and multi-criteria decision analysis (MCDA) methods are an important component of defining decision models. Despite their usefulness, there are still challenges in making robust decisions in dynamic environments due to the varying performance of different MCDA methods. It creates space for the development of techniques to aggregate conflicting results. This paper introduces a fuzzy ranking approach for aggregating results from multi-criteria assessments, specifically addressing the limitations of current result aggregation techniques. Unlike conventional methods, the proposed approach represents rankings as fuzzy sets, providing detailed insights into the robustness of decision problems. The study uses green supplier selection as a case study, examining the performance of the introduced approach and the robustness of its recommendations within the sustainability field. This study offers a new methodology for aggregating results from multiple evaluation scenarios, thereby enhancing decision-maker awareness and robustness. Through comparative analysis with traditional compromise solution methods, this paper highlights the limitations of current approaches and indicates the advantages of adopting fuzzy ranking aggregation. This study significantly advances the field of decision-making by enhancing the understanding of the stability of decision outcomes.

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A three-way decisions approach based on double hierarchy linguistic aggregation operators of strict t-norms and t-conorms

Zhong

Chen

et al. 2023

Int. J. Mach. Learn. & Cyber.

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With the massive increase in uncertainty of linguistic information in realistic decision making, there is a great challenge for people to make decisions in the complex linguistic environment. To overcome this challenge, this paper proposes a three-way decisions method based on aggregation operators of strict t-norms and t-conorms under double hierarchy linguistic environment. By mining the double hierarchy linguistic information, strict t-norms and t-conorms are introduced to define the operation rules and their operation examples are also given. Then, the double hierarchy linguistic weighted average (DHLWA) operator and weighted geometric (DHLWG) operator are proposed based on strict t-norms and t-conorms. Besides, some of their important properties are also proved and derived, such as idempotency, boundedness and monotonicity. Next, DHLWA and DHLWG are integrated with three-way decisions to construct our three-way decisions model. Specifically, the double hierarchy linguistic decision theoretic rough set (DHLDTRS) model is constructed by incorporating the computational model of expected loss with DHLWA and DHLWG, which can consider the various decision attitudes from decision makers more adequately. Furthermore, we also propose a novel entropy weight calculation formula to improve the entropy weight method for obtaining the weights more objectively, and integrate grey relational analysis (GRA) method to calculate the conditional probability. Based on the Bayesian minimum-loss decision rules, the solving method of our model is also propounded and the corresponding algorithm is designed. Finally, an illustrative example and experimental analysis are presented, which can validate the rationality, robustness as well as superiority of our method.

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Unbalanced double hierarchy linguistic group decision-making method based on SWARA and S-ARAS for multiple attribute group decision-making problems

Cited by 8 publications

References 44 publications

A novel IFN-CSM-CoCoSo approach for multiple-attribute group decision-making with intuitionistic fuzzy sets: An application in assessing corporate social responsibility performance

A novel IFN-CSM-CoCoSo approach for multiple-attribute group decision-making with intuitionistic fuzzy sets: An application in assessing corporate social responsibility performance

Toward robust decision-making under multiple evaluation scenarios with a novel fuzzy ranking approach: green supplier selection study case

A three-way decisions approach based on double hierarchy linguistic aggregation operators of strict t-norms and t-conorms

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