Multiplicative consistency analysis of linguistic preference relation with self‐confidence level and self‐doubting level and its application in a group decision making

Mandal, Prasenjit; Samanta, Sovan; Pal, Madhumangal

doi:10.1002/int.22516

Cited by 8 publications

(2 citation statements)

References 42 publications

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“…Step 1: Each experts or decision makers interacting each others using social network and then provide their performance with respect to either bipolar-valued fuzzy value [17][18][19][20] or fuzzy value [21].…”

Section: Introductionmentioning

confidence: 99%

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Dhanalakshmi¹,

Samanta²,

Sivaraman³

et al. 2023

Computer Systems Science and Engineering

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Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov's intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation process. Hesitant bipolar valued fuzzy set (HBVFS) is a generalization of HFS. This paper aims to introduce a general framework of multi-attribute group decision-making using social network. We propose two types of decision-making processes: Type-1 decision-making process and Type-2 decision-making process. In the Type-1 decision-making process, the experts' original opinion is proces for the final ranking of alternatives. In Type-2 decision making processs, there are two major aspects we consider. First, consistency tests and checking of consensus models are given for detecting that the judgments are logically rational. Otherwise, the framework demands (partial) decision-makers to review their assessments. Second, the coherence and consensus of several HBVFSs are established for final ranking of alternatives. The proposed framework is clarified by an example of software packages selection of a university.

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Section: Introductionmentioning

confidence: 99%

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Dhanalakshmi¹,

Samanta²,

Sivaraman³

et al. 2023

Computer Systems Science and Engineering

Self Cite

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“…These behaviors increase the chances of finding food and avoiding predators. Because of the extensive applications of flocking control in engineering, such as the formation of mobile robots and the cooperation of unmanned aerial vehicles, the interest in swarming problems is on the rise among control theorists [1–3].…”

Section: Introductionmentioning

confidence: 99%

Robust flocking of multiple intelligent agents with multiple disturbances

Yang

Chen

Yang

2022

Int J of Intelligent Sys

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The cooperation control of multiple intelligent agents (MIAs), which can solve complex engineering problems in practice, has received increasing attention. However, there are multiple disturbances in wireless sensor networks, which has a great effect on the collaboration of MIAs. In this paper, the problem of the flocking motion of second-order MIAs is addressed with collision avoidance and multiple disturbances. To estimate the matched/mismatched disturbances, the disturbance observers are designed. It is noted that the assumption that the differentials of disturbances converge to zeros in the literature is removed. A novel compound strategy is designed by using the robust auxiliary function and the potential function. The asymptotic properties of the flocking system are studied based on the Input-to-State Stability Theorem and the robust stability. Numerical simulation results verify the validity of the proposed protocol. K E Y W O R D S collision avoidance, distributed control protocol, multiple disturbances, multiple intelligent agents, robust flocking 1 | INTRODUCTION Recently, flocking behaviors have been studied by scholars from different fields, such as engineering, computer, and biology. Cooperative behaviors of multiple intelligent agents (MIAs) widely exist in the natural world, for example, the schooling of fish, flocking of birds, and swarming of bacteria. These behaviors increase the chances of finding food and avoiding

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Three-way decision model under a large-scale group decision-making environment with detecting and managing non-cooperative behaviors in consensus reaching process

Mandal

Samanta²,

Pal

et al. 2022

Artif Intell Rev

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Multiplicative consistency analysis of linguistic preference relation with self‐confidence level and self‐doubting level and its application in a group decision making

Abstract: This article focuses on a group decision-making (GDM) approach based on the multiplicative consistency of linguistic preference relation (LPR) with experts' self-

Cited by 8 publications

References 42 publications

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

Robust flocking of multiple intelligent agents with multiple disturbances

Three-way decision model under a large-scale group decision-making environment with detecting and managing non-cooperative behaviors in consensus reaching process

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