8,978 research outputs found
An optimal feedback model to prevent manipulation behaviours in consensus under social network group decision making
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.A novel framework to prevent manipulation behaviour
in consensus reaching process under social network
group decision making is proposed, which is based on a theoretically
sound optimal feedback model. The manipulation
behaviour classification is twofold: (1) âindividual manipulationâ
where each expert manipulates his/her own behaviour to achieve
higher importance degree (weight); and (2) âgroup manipulationâ
where a group of experts force inconsistent experts to adopt
specific recommendation advices obtained via the use of fixed
feedback parameter. To counteract âindividual manipulationâ, a
behavioural weights assignment method modelling sequential
attitude ranging from âdictatorshipâ to âdemocracyâ is developed,
and then a reasonable policy for group minimum adjustment cost
is established to assign appropriate weights to experts. To prevent
âgroup manipulationâ, an optimal feedback model with objective
function the individual adjustments cost and constraints related
to the threshold of group consensus is investigated. This approach
allows the inconsistent experts to balance group consensus and
adjustment cost, which enhances their willingness to adopt the
recommendation advices and consequently the group reaching
consensus on the decision making problem at hand. A numerical
example is presented to illustrate and verify the proposed optimal
feedback model
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
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
A double interaction-based financing group decisionmaking framework considering uncertain information and inconsistent assessment
Financing group decision-making (FGDM), which is an important
stage of project financing, has unique characteristics: large investments
and long payback horizons. Its evaluation results are likely
to be distorted if we ignore the uncertain information and inconsistent
assessment during the decision-making process. In this
study, we propose a double interaction-based FGDM framework
under uncertain information and inconsistent assessment. We
modify the weight setting of evidence reasoning and aggregation
method of probabilistic linguistic term sets to process the above
two issues. The proposed framework is applied in a detailed case
study analysis to display its effectiveness and stability. We expect
the double interaction-based group decision-making framework
under uncertain information and inconsistent assessment to be a
useful tool to understand FGDM processes
A General Overview of Multi-objective Multiple-participant Decision Making for Flood Management
Decision-making problems in water resources are often associated with multiple objectives and multiple stakeholders. To enable more effective and acceptable decision outcome, it is required that more participation is ensured in the decision making process. This is particularly relevant for flood management problems where the number of stakeholders could be very large. Although application of multi-objective decision-making tools in water resources is very wide, application with the consideration of multiple stakeholders is much more limited. The solution methodologies adapted for multi-objective multi-participant decision problems are generally based on aggregation of decisions obtained for individual decision makers. This approach seems somewhat inadequate when the number of stakeholders is very large, as often is the case in flood management.
The present study has been performed to have an overview of existing solution methodologies for multi-objective decision making approaches in water resources. Decision making by single and multiple stakeholders has been considered under both deterministic and uncertain conditions. It has been found that the use of fuzzy set theory to represent various uncertainties associated with decision making situations under multi-objective multiple-participant environment is very promising. Coupled with multi-objective methods (e. g. compromise programming and goal programming), fuzzy approach has also the ability to support group decisions, to reflect collective opinions and conflicting judgments.https://ir.lib.uwo.ca/wrrr/1003/thumbnail.jp
Fuzzy decision making: A bibliometric-based review
Fuzzy decision-making consists in making decisions under complex and uncertain environments where the information can be assessed with fuzzy sets and systems. The aim of this study is to review the main contributions in this field by using a bibliometric approach. For doing so, the article uses a wide range of bibliometric indicators including the citations and the h-index. Moreover, it also uses the VOS viewer software in order to map the main trends in this area. The work considers the leading journals, articles, authors and institutions. The results indicate that the USA was the traditional leader in this field with the most significant researcher. However, during the last years, this field is receiving more attention by Asian authors that are starting to lead the field. This discipline has a strong potential and the expectations for the future is that it will continue to grow
Combined probabilistic linguistic term set and ELECTRE II method for solving a venture capital project evaluation problem
Multiple criteria decision making (MCDM) frameworks assist people in assessing alternatives and making reasonable decisions,
with the ELECTRE II MCDM method in particular being widely
applied to many diverse fields. As it is not always possible to
assess qualitative attributes or accurately evaluate alternatives
using precise values, this paper proposes a new approach that combines the ELECTRE II method with probabilistic linguistic term sets
(PLTS) to allow decision makers to state their qualitative preferences
using corresponding probabilities. To demonstrate the viability of
the PTLS-ELECTRE II method and assess its practicability, the proposed method was applied to a typical MCDM venture capital project evaluation problem, for which a comprehensive venture capital
project evaluation index system was constructed that included multiple qualitative and quantitative indicators, such as industry background, marketing, product technology, team management and
financial data. The reasonable evaluation sequence of alternatives
was then determined using the PTLS-ELECTRE II method which can
provide more accurate MCDM decisions
The risk assessment of construction project investment based on prospect theory with linguistic preference orderings
Multiple experts decision-making (MEDM) can be regarded as a
situation where a group of experts are invited to provide their
opinions by evaluating the given alternatives, and then select the
optimal alternative(s). As a useful linguistic expression model, linguistic
preference orderings (LPOs) were established in which the
order of alternatives and the relationships between two adjacent
alternatives are fused well. Considering that prospect theory has
the superiority in depicting risk attitudes (risk seeking for losses
and risk aversion for gains) during the uncertain decision-making
process, this paper develops a consensus model based on prospect
theory to deal with MEDM problems with LPOs. Firstly, each
LPO provided by expert is transformed into the responding
DHLPR with complete consistency. Then, the reference point of
expert is determined and the prospect preference matrix is established.
Moreover, we can obtain the overall prospect consensus
degree for a MEDM problem by calculating the similarity degree
between individual and collective prospect preference matrix.
Furthermore, a consensus improvement method is developed to
complete the consensus reaching process. Finally, we apply the
proposed method to deal with a practical MEDM problem involving
the construction project investment, and make some comparative
analyses with existing methods.National Natural Science Foundation of China (NSFC)
71771155China Postdoctoral Science Foundation
2020M680151Sichuan Postdoctoral Science special FoundationSichuan University Postdoctoral Interdisciplinary Innovation Startup FoundationFundamental Research Funds for the Central Universities
YJ202015European Union (EU)
TIN2016-75850-RSichuan Province System Science and Enterprise Development Research Center
Xq20B0
- âŠ