A Comprehensive Literature Review of 50 Years of Fuzzy Set Theory

Kahraman, Cengiz; Öztayşi, Başar; Onar, Sezi Çevik

doi:10.1080/18756891.2016.1180817

Cited by 101 publications

(30 citation statements)

References 203 publications

(193 reference statements)

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“…We notice that the fuzzy method is prevalently used in mobile cloud offloading since this method is characterized by using linguistic variables to describe fuzzy terms that are then mapped to numerical variables [63][64][65]. Moreover, it deals effectively with uncertain and imprecise information to solve real-world problems in different domains such as bioenergy production technologies [66], cloud storage service [67], e-learning [68], microgrids [69,70], and so on.…”

Section: Uncertainty and Fuzzy Methodsmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

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Abstract:Mobile cloud computing (MCC) is becoming a popular mobile technology that aims to augment local resources of mobile devices, such as energy, computing, and storage, by using available cloud services and functionalities. The offloading process is one of the techniques used in MCC to enhance the capabilities of mobile devices by moving mobile data and computation-intensive operations to cloud platforms. Several techniques have been proposed to perform and improve the efficiency and effectiveness of the offloading process, such as multi-criteria decision analysis (MCDA). MCDA is a well-known concept that aims to select the best solution among several alternatives by evaluating multiple conflicting criteria, explicitly in decision making. However, as there are a variety of platforms and technologies in mobile cloud computing, it is still challenging for the offloading process to reach a satisfactory quality of service from the perspective of customers' computational service requests. Thus, in this paper, we conduct a literature review that leads to a better understanding of the usability of the MCDA methods in the offloading operation that is strongly reliant on the mobile environment, network operators, and cloud services. Furthermore, we discuss the challenges and opportunities of these MCDA techniques for offloading research in mobile cloud computing. Finally, we recommend a set of future research directions in MCDA used for the mobile cloud offloading process.

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Section: Uncertainty and Fuzzy Methodsmentioning

confidence: 99%

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Bangui

Bühnová

et al. 2017

JSAN

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“…EDAS has been extended to ordinary fuzzy EDAS by Keshavarz Ghorabaee et al (2016) to handle the MCDM problems under fuzzy environment. Fuzzy sets have a history starting from ordinary fuzzy sets and extending to other types of fuzzy sets as illustrated in Figure 1 (Kahraman et al 2015(Kahraman et al , 2016.…”

Section: Introductionmentioning

confidence: 99%

Intuitionistic Fuzzy Edas Method: An Application to Solid Waste Disposal Site Selection

Kahraman

Ghorabaee

Zavadskas

et al. 2017

Journal of Environmental Engineering and Landscape Management

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271

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Evaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included.

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“…Decision-making information provided by decision makers is often imprecise and uncertain because of a lack of data, time pressure, or the decision maker's limited attention and information-processing capabilities. Accordingly, research pertaining to multiple criteria decision analysis (MCDA) problems has often been performed within a fuzzy uncertain environment 1,4,11,18 .…”

Section: Introductionmentioning

confidence: 99%

Multiple Criteria Decision Analysis Using Correlation-Based Precedence Indices Within Pythagorean Fuzzy Uncertain Environments

Wang¹,

Chen²

2018

IJCIS

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The theory of Pythagorean fuzzy sets possesses significant advantages in handling vagueness and complex uncertainty. Additionally, Pythagorean fuzzy information is useful to simulate the ambiguous nature of subjective judgments and measure the fuzziness and imprecision more flexibly. The aim of this research is to develop an effective assignment-based method using a novel concept of correlation-based precedence indices for conducting multiple criteria decision analysis within the Pythagorean fuzzy uncertain environment. Based on the ideas of information energy and correlations, this paper defines a novel concept of correlation-based precedence indices in the Pythagorean fuzzy context and discusses their desirable properties. Next, this paper presents some useful concepts of discordance indicators, weighted discordance indicators, comprehensive discordance indicators, and comprehensive discordance indices to construct a novel assignment model for acquiring a comprehensive ranking of candidate alternatives. As an application of the proposed assignment-based method, a practical example concerning a financing decision of working capital policies is provided to demonstrate its practicality and effectiveness.

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A Comprehensive Literature Review of 50 Years of Fuzzy Set Theory

Cited by 101 publications

References 203 publications

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Multi-Criteria Decision Analysis Methods in the Mobile Cloud Offloading Paradigm

Intuitionistic Fuzzy Edas Method: An Application to Solid Waste Disposal Site Selection

Multiple Criteria Decision Analysis Using Correlation-Based Precedence Indices Within Pythagorean Fuzzy Uncertain Environments

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