187 research outputs found
A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
Interest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the field has been widely studied from several viewpoints and multiple approaches have been proposed. Nevertheless, there is a lack of general framework. Moreover, this problem is exacerbated in the case of expertsâ weighting methods, one of the most widely-used techniques to deal with multiple source aggregation. This lack of general classification scheme, or a guide to assist expert knowledge, leads to ambiguity or misreading for readers, who may be overwhelmed by the large amount of unclassified information currently available. To invert this situation, a general GDM framework is presented which divides and classifies all data aggregation techniques, focusing on and expanding the classification of expertsâ weighting methods in terms of analysis type by carrying out an in-depth literature review. Results are not only classified but analysed and discussed regarding multiple characteristics, such as MCDMs in which they are applied, type of data used, ideal solutions considered or when they are applied. Furthermore, general requirements supplement this analysis such as initial influence, or component division considerations. As a result, this paper provides not only a general classification scheme and a detailed analysis of expertsâ weighting methods but also a road map for researchers working on GDM topics or a guide for experts who use these methods. Furthermore, six significant contributions for future research pathways are provided in the conclusions.The first author acknowledges support from the Spanish Ministry of Universities [grant number FPU18/01471]. The second and third author wish to recognize their support from the Serra Hunter program. Finally, this work was supported by the Catalan agency AGAUR through its research group support program (2017SGR00227). This research is part of the R&D project IAQ4EDU, reference no. PID2020-117366RB-I00, funded by MCIN/AEI/10.13039/ 501100011033.Peer ReviewedPostprint (published version
Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information
The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the
intuitionistic fuzzy sets combines the classical decision method is in its
research and application is attracting attention. After comparative analysis,
there are multiple classical methods with IVIFSs information have been applied
into many practical issues. In this paper, we extended the classical EDAS
method based on cumulative prospect theory (CPT) considering the decision
makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain
character of the IVIFSs and the psychological preference into consideration,
the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method
is built for MAGDM issues. Meanwhile, information entropy method is used to
evaluate the attribute weight. Finally, a numerical example for project
selection of green technology venture capital has been given and some
comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some
comparison analysis and sensitivity analysis are applied to prove this new
methods effectiveness and stability.Comment: 48 page
Decision making with both diversity supporting and opposing membership information
Online big data provides large amounts of decision information
to decision makers, but supporting and opposing information are
present simultaneously. Dual hesitant fuzzy sets (DHFSs) are useful
models for exactly expressing the membership degree of both
supporting and opposing information in decision making.
However, the application of DHFSs requires an improved distance
measure. This paper aims to improve distance measure models
for DHFSs and apply the new distance models to generate a technique
for order preference by similarity to an ideal solution
(TOPSIS) method for multiple attribute decision making (MADM)
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
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
Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets
Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures â that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc
An overview of fuzzy multi-criteria decisionmaking methods in hospitality and tourism industries: bibliometrics, methodologies, applications and future directions
Stakeholders in hospitality and tourism industries are involved in
many decision-making scenarios. Multi-criteria decision-making
(MCDM) methods have been widely used in hospitality and tourism
industries. Although some articles summarised the applications of
MCDM models in hospitality and tourism industries, they ignored the
fuzziness of individual cognition in an uncertain environment. In addition,
these surveys lacked a comprehensive overview from the perspective
of bibliometrics analysis and content analysis regarding the
whole hospitality and tourism industries. To analyse the applications
of fuzzy MCDM methods in hospitality and tourism industries and
further explore future research directions, this article reviews 85
selected papers published from 1997 to 2022 regarding fuzzy MCDM
models applied in hospitality and tourism industries. Through analysing
the results of bibliometric analysis, methodologies and applications,
we found that analytic hierarchy process (AHP) and TOPSIS
methods are the most widely used MCDM methods, and tourism
evaluation, hotel evaluation and selection, tourism destination evaluation
and selection are the most attractive research issues in hospitality
and tourism industries. Finally, future research directions are
proposed from three aspects. This article provides insights for
researchers and practitioners who have interest in fuzzy MCDM models
in hospitality and tourism industries
A Multi-criteria Picture Fuzzy Decision-making Model for Green Supplier Selection based on Fractional Programming
Due to the increasing complexity in green supplier selection, there would be some important issues for expressing inherent uncertainty or imprecision of decision makersâ cognitive information in decision making process. As an extension of intuitionistic fuzzy sets (IFSs) and neutrosophic sets (NSs), picture fuzzy sets (PFSs) can better model and represent the hesitancy and uncertainty of decision makersâ preference information. In this study, an attempt has been made to present a multi-criteria picture fuzzy decision-making model for green supplier selection based on fractional programming. In this approach, the ratings of alternatives and weights of criteria are represented by PFSs and IFSs, respectively. Based on the available information, some pairs of fractional programming models are derived from the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the proposed biparametric picture fuzzy distance measure to determine the relative closeness coefficient intervals of green suppliers, which are aggregated for the criteria to generate the ranking order of all green suppliers by computing their optimal degrees of membership based on the ranking method of interval numbers. Finally, an example is conducted to validate the effectiveness of the proposed multi-criteria decision making (MCMD) method
New Challenges in Neutrosophic Theory and Applications
Neutrosophic theory has representatives on all continents and, therefore, it can be said to be a universal theory. On the other hand, according to the three volumes of âThe Encyclopedia of Neutrosophic Researchersâ (2016, 2018, 2019), plus numerous others not yet included in Encyclopedia book series, about 1200 researchers from 73 countries have applied both the neutrosophic theory and method. Neutrosophic theory was founded by Professor Florentin Smarandache in 1998; it constitutes further generalization of fuzzy and intuitionistic fuzzy theories. The key distinction between the neutrosophic set/logic and other types of sets/logics lies in the introduction of the degree of indeterminacy/neutrality (I) as an independent component in the neutrosophic set. Thus, neutrosophic theory involves the degree of membership-truth (T), the degree of indeterminacy (I), and the degree of non-membership-falsehood (F). In recent years, the field of neutrosophic set, logic, measure, probability and statistics, precalculus and calculus, etc., and their applications in multiple fields have been extended and applied in various fields, such as communication, management, and information technology. We believe that this book serves as useful guidance for learning about the current progress in neutrosophic theories. In total, 22 studies have been presented and reflect the call of the thematic vision. The contents of each study included in the volume are briefly described as follows. The first contribution, authored by Wadei Al-Omeri and Saeid Jafari, addresses the concept of generalized neutrosophic pre-closed sets and generalized neutrosophic pre-open sets in neutrosophic topological spaces. In the article âDesign of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distributionâ, the authors Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, and Abdur Razzaque Mughal discuss the use of probability distribution function of BirnbaumâSaunders distribution as a proportion of defective items and the acceptance probability in a fuzzy environment. Further, the authors Derya Bakbak, Vakkas Uluc¸ay, and Memet S¸ahin present the âNeutrosophic Soft Expert Multiset and Their Application to Multiple Criteria Decision Makingâ together with several operations defined for them and their important algebraic properties. In âNeutrosophic Multigroups and Applicationsâ, Vakkas Uluc¸ay and Memet S¸ahin propose an algebraic structure on neutrosophic multisets called neutrosophic multigroups, deriving their basic properties and giving some applications to group theory. Changxing Fan, Jun Ye, Sheng Feng, En Fan, and Keli Hu introduce the âMulti-Criteria Decision-Making Method Using Heronian Mean Operators under a Bipolar Neutrosophic Environmentâ and test the effectiveness of their new methods. Another decision-making study upon an everyday life issue which empowered us to organize the key objective of the industry developing is given in âNeutrosophic Cubic Einstein Hybrid Geometric Aggregation Operators with Application in Prioritization Using Multiple Attribute Decision-Making Methodâ written by Khaleed Alhazaymeh, Muhammad Gulistan, Majid Khan, and Seifedine Kadry
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