Multi-criteria group decision making with fuzzy logic and entropy based weighting

Cui, Zhu Xian; Yoo, Han Ku; Choi, Jun Yeol; Youn, Hee Yong

doi:10.1145/1968613.1968706

Cited by 13 publications

(12 citation statements)

References 17 publications

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“…Moreover, the existing method that used subjective weight has a weakness . The fuzziness and the vagueness of human judgment and preference make it difficult to be applied in practice [18]. Therefo re, this paper proposes second modification by introducing objective weight in interval type-2 fuzzy TOPSIS.…”

Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

“…Specifically entropy weight is proposed to use as the method of finding weight for sub-criteria in interval type-2 fu zzy TOPSIS. The idea of entropy method that used by Cui [18] is employed in this proposed method.…”

Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

“…Based on (9), the average decision matrix is constructed as follows: Step 7: Based on (18) and (19), we can get the distance between each alternative and ideal solution.…”

Section: C1 C2 C3mentioning

confidence: 99%

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A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Abdullah

Otheman²

2013

IJISA

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Abstract-Fuzzy Technique for Order Preference bySimilarly to Ideal Solution (TOPSIS) is one of the most commonly used approaches in solving numerous mu ltip le criteria decision making problems. It has been widely used in ranking of mu lt iple alternatives with respect to mu ltiple criteria with the superiority of fu zzy set type-1 and subjective weights. Recently, fu zzy TOPSIS has been merged with interval type-2 fu zzy sets and subjective weights for criteria as to handle the wide arrays of vagueness and uncertainty. However, the role of ob jective weights in this new interval type-2 fuzzy TOPSIS has given considerably less attention. This paper aims to propose a new objective weight for sub-criteria in interval type-2 fu zzy TOPSIS. Instead of using weight for criteria, this paper considers entropy weights for sub-criteria in interval type-2 fu zzy TOPSIS method. An example of supplier select ion is used to illustrate the proposed method.

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Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

Section: One Of the Well Known Methods In Multi Criteria Decision Makmentioning

confidence: 99%

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A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Abdullah

Otheman²

2013

IJISA

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“…Recently, in order to analyze the collective decision-making process, a lot of studies have been conducted [12]- [17]. Li et al introduced a distributed protocol for the collective decision making [12].…”

Section: A Collective Decision-making Analysis and Modelingmentioning

confidence: 99%

“…Sánchez-Anguix et al analyzed how environmental conditions affect different intrateam strategies in order to provide teams with the knowledge to select the proper intrateam strategy [16]. Cui et al presented a multicriteria group decision-making approach which employed the fuzzy theory and the entropy-based method [17].…”

Section: A Collective Decision-making Analysis and Modelingmentioning

confidence: 99%

Analyzing Social Roles Based on a Hierarchical Model and Data Mining for Collective Decision-Making Support

Zhou

Jin

et al. 2017

IEEE Systems Journal

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With the popularity of social networking services (SNSs) and the increase of users, individuals' social roles in a social network have become more and more important in terms of the recommendation of personalized services and the collective decision-making process. Usually, in an SNS system, active users may not represent the major opinions among the whole users, and most of the users' opinions may be multifarious. In this paper, we focus on analyzing and identifying users' dynamical social roles to facilitate the collective decision-making process. After introducing the social choice theory and an improved collective decision-making model, we present a three-layer model to analyze users' social roles in a hierarchical way and develop an integrated mechanism to utilize the identification of social roles to support the collective decision making. Based on a developed NetLogo-based tool, a case study for the course-offering determination with an application scenario is demonstrated to show the process of using users' social roles to support the collective decision making. The comparison experiment conducted between our method and the Delphi method shows the usefulness of our proposed method to help users achieve the decision consensus in a more efficient way. He has been engaged extensively in research works in the fields of computer science, information systems, and social and human informatics. He seeks to exploit the rich interdependence between theory and practice in his work with interdisciplinary and integrated approaches. His recent research interests cover human-centric ubiquitous computing, human-computer interaction, behavior and cognitive informatics, big data, personal analytics and individual modeling, MOOCs and learning analytics, and computing for well-being.Prof. Jin is a member of IEEE CS and ACM USA; IEICE, IPSJ, and JSAI Japan; and CCF China.Fuhua Lin received the Ph.D. degree in industry engineering and engineering management from the

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Multi-distance and Fuzzy Similarity Based Fuzzy TOPSIS

Collan

Fedrizzi

Luukka

2015

Studies in Computational Intelligence

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Multi-criteria group decision making with fuzzy logic and entropy based weighting

Cited by 13 publications

References 17 publications

A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Analyzing Social Roles Based on a Hierarchical Model and Data Mining for Collective Decision-Making Support

Multi-distance and Fuzzy Similarity Based Fuzzy TOPSIS

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