1,727 research outputs found
Pythagorean 2-tuple linguistic power aggregation operators in multiple attribute decision making
In this paper, we investigate the multiple attribute decision making
problems with Pythagorean 2-tuple linguistic information.
Then, we utilize power average and power geometric operations
to develop some Pythagorean 2-tuple linguistic power aggregation
operators: Pythagorean 2-tuple linguistic power weighted
average (P2TLPWA) operator, Pythagorean 2-tuple linguistic power
weighted geometric (P2TLPWG) operator, Pythagorean 2-tuple linguistic
power ordered weighted average (P2TLPOWA) operator,
Pythagorean 2-tuple linguistic power ordered weighted geometric
(P2TLPOWG) operator, Pythagorean 2-tuple linguistic power
hybrid average (P2TLPHA) operator and Pythagorean 2-tuple linguistic
power hybrid geometric (P2TLPHG) operator. The prominent
characteristic of these proposed operators are studied. Then,
we have utilized these operators to develop some approaches to
solve the Pythagorean 2-tuple linguistic multiple attribute decision
making problems. Finally, a practical example for enterprise
resource planning (ERP) system selection is given to verify the
developed approach and to demonstrate its practicality and
effectiveness
CODAS methods for multiple attribute group decision making with interval-valued bipolar uncertain linguistic information and their application to risk assessment of Chinese enterprises’ overseas mergers and acquisitions
Bipolar fuzzy set theory has been successfully applied in some
areas, but there are situations in real life which can’t be represented by bipolar fuzzy sets. However, all the existing approaches
are unsuitable to describe the positive and negative membership
degree an element to an uncertain linguistic label to have an
interval value, which can reflect the decision maker’s confidence
level when they are making an evaluation. In order to overcome
this limit, we propose the definition of interval-valued bipolar
uncertain linguistic sets (IVBULSs) to solve this problem based on
the bipolar fuzzy sets and uncertain linguistic information processing models. In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain
linguistic sets (IVBULSs) and propose some IVBUL aggregating
operators. Then, we extend the CODAS method to solve multiple
attribute group decision making (MAGDM) issues with interval-valued bipolar uncertain linguistic numbers (IVBULNs) based on
these operators. An example for risk assessment of Chinese enterprises’ overseas mergers and acquisitions (M&As) is given to illustrate the proposed methodology
Fuzzy Techniques for Decision Making 2018
Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches
The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information
In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure
Algorithms for probabilistic uncertain linguistic multiple attribute group decision making based on the GRA and CRITIC method: application to location planning of electric vehicle charging stations
Electric vehicles (EVs) could be regarded as one of the most
innovative and high technologies all over the world to cope with
the fossil fuel energy resource crisis and environmental pollution
issues. As the initiatory task of EV charging station (EVCS) construction,
site selection play an important part throughout the
whole life cycle, which is deemed to be multiple attribute group
decision making (MAGDM) problem involving many experts and
many conflicting attributes. In this paper, a grey relational analysis
(GRA) method is investigated to tackle the probabilistic uncertain
linguistic MAGDM in which the attribute weights are completely
unknown information. Firstly, the definition of the expected value
is then employed to objectively derive the attribute weights
based on the CRiteria Importance Through Intercriteria Correlation
(CRITIC) method. Then, the optimal alternative is chosen by calculating
largest relative relational degree from the probabilistic
uncertain linguistic positive ideal solution (PULPIS) which considers
both the largest grey relational coefficient from the PULPIS and the
smallest grey relational coefficient from the probabilistic uncertain
linguistic negative ideal solution (PULNIS). Finally, a numerical
case for site selection of electric vehicle charging stations (EVCS) is
designed to illustrate the proposed method. The result shows the
approach is simple, effective and easy to calculate
The generalized dice similarity measures for multiple attribute decision making with hesitant fuzzy linguistic information
In this paper, we shall present some novel Dice similarity measures of hesitant fuzzy linguistic term sets and the generalized Dice similarity measures of hesitant fuzzy linguistic term sets and indicate that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute decision making models with hesitant fuzzy linguistic term sets. Finally, a practical example concerning the evaluation of the quality of movies is given to illustrate the applicability and advantage of the proposed generalized Dice similarity measure
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039
71421001,71910107002,71771037,71874023
71871149Sichuan University sksyl201705
2018hhs-5
VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications
The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique
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