Group decision making using incomplete fuzzy preference relations based on the additive consistency and the order consistency

Chen, Shyi‐Ming; Lin, Tsung-En; Lee, Li-Wei

doi:10.1016/j.ins.2013.08.042

Cited by 127 publications

(44 citation statements)

References 26 publications

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“…Subsequently, Chen [8] proposed a new method to solve the problem about the consistency of the order in fuzzy preference relations.…”

Section: Fuzzy Preference Relationsmentioning

confidence: 99%

A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

Liu¹,

Wang²

2018

Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)

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Abstract:The multi-sensor data fusion technique plays a significant role in fault diagnosis and in a variety of applications. Conflict management is an open issue in Dempster-Shafer evidence theory. In this paper, a novel multi-sensor data fusion approach is proposed based on the spectral angle cosine function of evidence, belief entropy and group decision fuzzy preference relation analysis.The numerical simulation analyses demonstrate that the improved DS evidence theory available in this paper overcomes the limitations of conventional DS evidence theory, and can realizes more reliable fusion with multi-sensor conflicting information compared to the existing methods.

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“…Subsequently, Chen [8] proposed a new method to solve the problem about the consistency of the order in fuzzy preference relations.…”

Section: Fuzzy Preference Relationsmentioning

confidence: 99%

A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

Liu¹,

Wang²

2018

Proceedings of the 2017 4th International Conference on Machinery, Materials and Computer (MACMC 2017)

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“…Definition 7 [23]: Define the consistency degree between fuzzy preference relation and consistency matrix as:…”

Section: Fuzzy Preference Relations and Consistency Degreementioning

confidence: 99%

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

Yuan¹,

Li²

2017

Open Cyber

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Abstract:In order to restore power to out-of-service areas quickly, this paper proposes a new service restoration decision-making algorithm for a distribution network. First, using heuristic rules, a candidate service restoration scheme set is generated. Considering the target of service restoration, five evaluation indices are introduced, including the quantities of restored load and transferred load, the margin of load capacity, the rate of load balancing, and the switching times of circuit breakers. Second, because of the problem of fuzzy measure identification, interaction between attributes, and the requirements for consistency with group decision making, this study defines the Shapley value identification method based on the Mahalanobis-Taguchi system and interval fuzzy preference relations. The fuzzy measure is obtained by the Shapley value, and the decision-making model is constructed by the Choquet integral with φs transformation function. Finally, an example application proves that the method is feasible and effective for decision making. Compared with the other method, the results verify the superiority of the decision process and show that it is consistent with the real conditions of post-fault restoration in a smart distribution network.

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“…Their view is revised and further enhanced in Büyüközkan and Ç ifçi's [3] study, where it is considered as a GDM approach within individual assessments. More recently, Chen and his colleagues [34] presented a new model for GDM including incomplete information based on additive consistency to overcome the drawbacks of Lee's method.…”

Section: Incomplete Preference Relations and Gdm In Qfdmentioning

confidence: 99%

“…DMs may have their own opinions and background, which enable them to assess problems from different perspectives. To minimize bias and partiality in the decision making process, assessments of multiple DMs (i.e., GDM) can be used together, which is preferrable to a single DM [6,[9][10][11][12][13]. Despite differences, DMs have common interest in agreeing on the most suitable alternative [4,6].…”

Section: Introductionmentioning

confidence: 99%

Extending Fuzzy QFD Methodology with GDM Approaches: An Application for IT Planning in Collaborative Product Development

Büyüközkan

Güleryüz

2015

Int. J. Fuzzy Syst.

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Collaborative product development (CPD) is a technology intensive process and effective planning in information technologies (IT) can improve the performance of CPD activities. Considering that quality function deployment (QFD) can be utilized as a planning tool for products and systems, the use of the QFD can enable IT systems to align their structure for CPD. In the QFD approach, the house of quality matrix is used for converting customer requirements into engineering characteristics. The challenge in this process is the profile of the inputs that are collected from the participants who provide feedback on customer requirements. Individual judgments of these participants can be in various formats, or can indicate preferences that are incomplete. This study aims to tackle with this issue by making use of an extended QFD methodology in CPD for IT planning. For this purpose, two group decision making (GDM) approaches are used to address both challenges of multiple preference formats and incomplete information. The validity of the developed IT planning model for CPD is tested with a case study at a Turkish software company using the two GDM approaches, and the obtained results are discussed. As customer requirements are important at every phase of CPD, the proposed model can help implementers to improve their decision processes.

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Group decision making using incomplete fuzzy preference relations based on the additive consistency and the order consistency

Cited by 127 publications

References 26 publications

A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

A Novel Method of DS Evidence Theory for Multi-Sensor Conflicting Information

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

Extending Fuzzy QFD Methodology with GDM Approaches: An Application for IT Planning in Collaborative Product Development

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