Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making

Jin, Feifei; Pei, Lidan; Chen, Huayou; Zhou, Ligang

doi:10.1016/j.knosys.2014.01.014

Cited by 105 publications

(36 citation statements)

References 28 publications

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“…Secondary vertical shock absorber V 13 Railway coupling V 14 Gearbox V 15 Grounding device V 16 Traction motor V 17 Height adjusting device V 18 Antihunting damper V 19 Air spring V 20 Center pin bush V 21 Traction rod V 22 Transverse shock absorber V 23 Transverse backstop V 24 Anti-side-rolling torsion bar V 25 Control valve V 26 Speed Sensor 1 V 27 Speed Sensor 2 V 28 LKJ2000 V 29 Device for cleaning the tread band of vehicle wheels V 30 Acceleration sensor V 31 Junction box V 32 Temperature sensor bearing V 33 Axle temperature sensor…”

Section: A Case Study and Discussionmentioning

confidence: 99%

“…In recent years, researchers study a multiattribute ranking problem to evaluate the component importance comprehensively from more than one perspective, which would be a special case of multicriteria decisionmaking (MCDM). MCDM refers to making decision for alternatives in the presence of multiple and conflicting criteria [18] and has many developments and applications, such as extensions of TOPSIS [19,20], Analytic Hierarchy Process [21], -shell decomposition [22], and entropy theory [23]. Detailed descriptions and mathematical expressions for multicriteria decision-making approaches can be found in Govindan et al [24].…”

Section: Previous Workmentioning

confidence: 99%

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Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

Lin

Wang

Jia

et al. 2017

Discrete Dynamics in Nature and Society

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In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components.

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Section: A Case Study and Discussionmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

Lin

Wang

Jia

et al. 2017

Discrete Dynamics in Nature and Society

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“…Jin et al (2014) introduced the interval-valued intuitionistic fuzzy continuous weighted entropy and established an approach to MCGDM. One emergency risk management (ERM) evaluation was provided to illustrate the application of the developed approach.…”

Section: Entropy and Cross-entropy Measuresmentioning

confidence: 99%

“…In fact, all of these aggregation operations can be considered as granules in granular computing (GrC) (Pedrycz and Chen 2015;Peters and Weber 2016;Livi and Sadeghian 2016;Xu and Wang 2016;Antonelli et al 2016;Lingras et al 2016;Skowron et al 2016;Dubois and Prade 2016;Loia et al 2016;Yao 2016;Ciucci 2016;Wilke and Portmann 2016;Song and Wang 2016;Liu et al 2016). Based on these aggregation operators, many decisionmaking approaches have been put forward to deal with different kinds of decision-making problems with intervalvalued intuitionistic fuzzy information (Gu et al 2014;Zhao et al 2013;Jin et al 2014;Ye 2011;Wei and Zhang 2015;Gupta et al 2015;Xu and Shen 2014;Wu and Chiclana 2014;Cai and Han 2014;Yue and Jia 2013;Chen et al 2011Chen et al , 2012Xiao and Wei 2008;Zhang et al 2013;Chen and Li 2013;Chen and Chiou 2015), such as the extended VIKOR method (Zhao et al 2013), the entropy measures (Jin et al 2014;Ye 2011;Wei and Zhang 2015;Gupta et al 2015), the outranking choice method , the inclusion-based LINMAP method ) and the risk attitudinal ranking method (Wu and Chiclana 2014), the evidential reasoning methodology (Chen and Chiou 2015), etc. To understand and learn these aggregation operators and de...…”

Section: Introductionmentioning

confidence: 99%

An overview of interval-valued intuitionistic fuzzy information aggregations and applications

Zhang

Gou

2016

Granul. Comput.

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Interval-valued intuitionistic fuzzy set, generalized by Atanassov and Gargov, can be used to characterize the uncertain information more sufficiently and accurately when we face the fact that the values of the membership function and the non-membership function in an intuitionistic fuzzy set are difficult to be expressed as exact real numbers in many real-world decision-making problems. In this paper, we provide an overview of interval-valued intuitionistic fuzzy information aggregation techniques, and their applications in various fields such as decisionmaking, entropy measure, supplier selection and some practical decision-making problems. Meanwhile, we also review some important methods for decision-making with interval-valued intuitionistic fuzzy information, including the QUALIFLEX-based method, the TOPSIS method, the extended VIKOR method, the module partition schemes evaluation (MPSE) approach, the outranking choice method, the inclusion-based LINMAP method and the risk attitudinal ranking method, the evidential reasoning methodology, etc. Finally, we point out some possible directions for future research.

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“…Wang and Liu [10] proposed new Einstein aggregation operators based on sum, exponent, and product theories and demonstrated the same for selecting better propulsion systems. Following this, some researchers have also formulated new IVIF based entropy measures for solving pattern recognition and GDM problems [11][12][13]. Also, new distance measures under IVIF context have attracted authors that provide effective GDM process [14,15].…”

Section: Introductionmentioning

confidence: 99%

A Scientific Decision Framework for Supplier Selection under Interval Valued Intuitionistic Fuzzy Environment

Krishankumar

Ravichandran

Ramprakash

2017

Mathematical Problems in Engineering

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This paper proposes a new scientific decision framework (SDF) under interval valued intuitionistic fuzzy (IVIF) environment for supplier selection (SS). The framework consists of two phases, where, in the first phase, criteria weights are estimated in a sensible manner using newly proposed IVIF based statistical variance (SV) method and, in the second phase, the suitable supplier is selected using ELECTRE (ELimination and Choice Expressing REality) ranking method under IVIF environment. This method involves three categories of outranking, namely, strong, moderate, and weak. Previous studies on ELECTRE ranking reveal that scholars have only used two categories of outranking, namely, strong and weak, in the formulation of IVIF based ELECTRE, which eventually aggravates fuzziness and vagueness in decision making process due to the potential loss of information. Motivated by this challenge, third outranking category, called moderate, is proposed, which considerably reduces the loss of information by improving checks to the concordance and discordance matrices. Thus, in this paper, IVIF-ELECTRE (IVIFE) method is presented and popular TOPSIS method is integrated with IVIFE for obtaining a linear ranking. Finally, the practicality of the proposed framework is demonstrated using SS example and the strength of proposed SDF is realized by comparing the framework with other similar methods.

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Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making

Cited by 105 publications

References 28 publications

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

An overview of interval-valued intuitionistic fuzzy information aggregations and applications

A Scientific Decision Framework for Supplier Selection under Interval Valued Intuitionistic Fuzzy Environment

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