Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making

Juyal, Divya; Kumar, Sanjay

doi:10.1016/j.ejor.2015.06.047

Cited by 271 publications

(107 citation statements)

References 43 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%

“…CMs of nodes in the holistic topological network are necessary to construct improved centrality measures to assess influential components. According to (20) and complex network theory, we can obtain centrality measures of all nodes, such as BC, CC, DC, and EC in (4)∼(7). Figure 6 shows the results of CMs in the network.…”

Section: Icms For Bogiementioning

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%

“…The attributes of edges and nodes in (20) are calculated according to the equation in Section 2.1. Related data, which is necessary for calculation, can be collected from historical failure databases and expert elicitation.…”

Section: The Network Model and Related Datamentioning

confidence: 99%

See 3 more Smart Citations

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: Icms For Bogiementioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Section: The Network Model and Related Datamentioning

confidence: 99%

See 2 more Smart Citations

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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“…Since the proposal of the concept, it has attracted much attention of researchers in related fields [26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

A Hesitant Fuzzy Linguistic Multicriteria Decision‐Making Method with Interactive Criteria and Its Application to Renewable Energy Projects Selection

Xiao

Cai

Wang

2017

Mathematical Problems in Engineering

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A variety of multicriteria decision-making (MCDM) methods for renewable energy projects evaluation have been proposed, of which the premise of using these methods is to assume that the criteria are independent of each other. However, it may be difficult or costly to build independent criteria set in some cases because renewable energy planning is to pursue a balance of economic, social, and environmental goals, which makes the existence of interaction among criteria be of great possibility. In this paper, we consider a highly ambiguous decision situation, where the experts are allowed to give the evaluations in the form of hesitant fuzzy linguistic terms set (HFLTS). We build a hesitant fuzzy linguistic decision-making model handling the interaction among criteria from the perspective of distance measure and apply it to renewable energy projects selection. The proposed method can consider more fuzzy factors and deal with the interaction among criteria more approximately. It can reduce the decision pressure and improve the decision-making efficiency because the decision makers are allowed to express their preference in form of HFLTS and a decision criteria set of which the criteria are independent of each other is not necessary.

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Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making

Peng

Yang

2016

Int. J. Intell. Syst.

293

155

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In this paper, we define the Choquet integral operator for Pythagorean fuzzy aggregation operators, such as Pythagorean fuzzy Choquet integral average (PFCIA) operator and Pythagorean fuzzy Choquet integral geometric (PFCIG) operator. The operators not only consider the importance of the elements or their ordered positions but also can reflect the correlations among the elements or their ordered positions. It is worth pointing out that most of the existing Pythagorean fuzzy aggregation operators are special cases of our operators. Meanwhile, some basic properties are discussed in detail. Later, we propose two approaches to multiple attribute group decision making with attributes involving dependent and independent by the PFCIA operator and multi-attributive border approximation area comparison (MABAC) in Pythagorean fuzzy environment. Finally, two illustrative examples have also been taken in the present study to verify the developed approaches and to demonstrate their practicality and effectiveness. C 2016 Wiley Periodicals, Inc.

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Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making

Cited by 271 publications

References 43 publications

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

A Hesitant Fuzzy Linguistic Multicriteria Decision‐Making Method with Interactive Criteria and Its Application to Renewable Energy Projects Selection

Pythagorean Fuzzy Choquet Integral Based MABAC Method for Multiple Attribute Group Decision Making

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