877 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 experts’ 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 experts’ 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 experts’ 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
Ordering based decision making: a survey
Decision making is the crucial step in many real applications such as organization management, financial planning, products evaluation and recommendation. Rational decision making is to select an alternative from a set of different ones which has the best utility (i.e., maximally satisfies given criteria, objectives, or preferences). In many cases, decision making is to order alternatives and select one or a few among the top of the ranking. Orderings provide a natural and effective way for representing indeterminate situations which are pervasive in commonsense reasoning. Ordering based decision making is then to find the suitable method for evaluating candidates or ranking alternatives based on provided ordinal information and criteria, and this in many cases is to rank alternatives based on qualitative ordering information. In this paper, we discuss the importance and research aspects of ordering based decision making, and review the existing ordering based decision making theories and methods along with some future research directions
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) ‘individual manipulation’
where each expert manipulates his/her own behaviour to achieve
higher importance degree (weight); and (2) ‘group manipulation’
where a group of experts force inconsistent experts to adopt
specific recommendation advices obtained via the use of fixed
feedback parameter. To counteract ‘individual manipulation’, a
behavioural weights assignment method modelling sequential
attitude ranging from ‘dictatorship’ to ‘democracy’ is developed,
and then a reasonable policy for group minimum adjustment cost
is established to assign appropriate weights to experts. To prevent
‘group manipulation’, 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
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
Granular computing and optimization model-based method for large-scale group decision-making and its application
In large-scale group decision-making process, some decision makers hesitate among several linguistic terms and cannot compare
some alternatives, so they often express evaluation information
with incomplete hesitant fuzzy linguistic preference relations.
How to obtain suitable large-scale group decision-making results
from incomplete preference information is an important and
interesting issue to concern about. After analyzing the existing
researches, we find that: i) the premise that complete preference
relation is perfectly consistent is too strict, ii) deleting all incomplete linguistic preference relations that cannot be fully completed will lose valid assessment information, iii) semantics given
by decision makers are greatly possible to be changed during the
consistency improving process. In order to solve these issues, this
work proposes a novel method based on Granular computing
and optimization model for large-scale group decision-making,
considering the original consistency of incomplete hesitant fuzzy
linguistic preference relation and improving its consistency without changing semantics during the completion process. An illustrative example and simulation experiments demonstrate the
rationality and advantages of the proposed method: i) semantics
are not changed during the consistency improving process, ii)
completion process does not significantly alter the inherent quality of information, iii) complete preference relations are globally
consistent, iv) final large-scale group decision-making result is
acquired by fusing complete preference relations with different weights
Introducing disruption on stagnated Group Decision Making processes using Fuzzy Ontologies
In Group Decision Making processes, experts debate about how to rank a set of alternatives. It is usual
that, at a certain point of the discussion, the debate gets stuck. In this paper, a novel Group Decision
Making method for environments with a high number of alternatives is presented. Fuzzy Ontologies
are used in order to represent the alternatives and their characteristics. Moreover, a novel stagnation
analysis is used in order to determine if the debate gets stuck. If it does, the method modifies the
alternatives set in order to introduce new options and remove the least popular ones. This way, the
debate can revive since that the new alternatives provide different points of view. The presented method helps experts to conduct long and thorough debates in order for them to be able to make
effective and reliable decisions.MCIN/AEI PID2019-103880RB-I00FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades B-TIC-590-UGR20Andalusian government P20_00673Ministry of Education and King Abdulaziz University, DSR, Jeddah, Saudi Arabia IFPHI-049-135-2020Universidad de Granada/CBU
WEBIRA - comparative analysis of weight balancing method
The attributes weight establishing problem is one of the most important MCDM tasks. This study summarizes weight determining approach which is called WEBIRA (WEight Balancing Indicator Ranks Accordance). This method requires to solve complicated optimization problem and its application is possible by carrying out non trivial calculations. The efficiency of WEBIRA and other MCDM methods – SAW (Simple Additive Weighting) and EMDCW (Entropy Method for Determining the Criterion Weight) compared for 4 different data normalization methods. The re-sults of the study revealed that more sophisticated WEBIRA method is significantly efficient for all considered numbers of alternatives. Efficiency of all methods decreases with increasing number of alternatives, but WEBIRA is still applicable, while appli-cation of other methods is impossible as the number of alternatives is greater than 11. WEBIRA is the least affected by the data normalization, while EMDCW is the most affected method
On Incomplete Fuzzy and Multiplicative Preference Relations In Multi-Person Decision Making
This research work has been developed with the financing of FEDER funds in FUZZYLING-II Project TIN2010-
17876, the Andalusian Excellence Projects TIC-05299 and TIC-5991 and the mobility grant program awarded by the University of Granada ’s International Office.2nd International Conference on Information Technology and Quantitative Management,
ITQM 2014Rapid changes in the business environment such us the globalization as well as the increasing necessity to make crucial decisions involving a huge range of alternatives in short period of time or even in real time have made that computerized group decision support systems become very useful tools. However in the majority of the cases the panel of experts cannot provide all the information about their preferences due to different reasons such as lack of knowledge, time etc. Therefore different approaches have been presented to deal with the missing preferences in group decision making contexts. In this paper we review and analyse the state-of-the-art research efforts carried out on this topic for incomplete fuzzy preference relations and multiplicative preference relations.FEDER funds in FUZZYLING-II Project TIN2010- 17876Andalusian Excellence Projects TIC-05299 and TIC-5991Mobility grant program awarded by the University of Granada ’s International Offic
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