1,176 research outputs found
Consistency and Consensus Driven for Hesitant Fuzzy Linguistic Decision Making with Pairwise Comparisons
Hesitant fuzzy linguistic preference relation (HFLPR) is of interest because
it provides an efficient way for opinion expression under uncertainty. For
enhancing the theory of decision making with HFLPR, the paper introduces an
algorithm for group decision making with HFLPRs based on the acceptable
consistency and consensus measurements, which involves (1) defining a hesitant
fuzzy linguistic geometric consistency index (HFLGCI) and proposing a procedure
for consistency checking and inconsistency improving for HFLPR; (2) measuring
the group consensus based on the similarity between the original individual
HFLPRs and the overall perfect HFLPR, then establishing a procedure for
consensus ensuring including the determination of decision-makers weights. The
convergence and monotonicity of the proposed two procedures have been proved.
Some experiments are furtherly performed to investigate the critical values of
the defined HFLGCI, and comparative analyses are conducted to show the
effectiveness of the proposed algorithm. A case concerning the performance
evaluation of venture capital guiding funds is given to illustrate the
availability of the proposed algorithm. As an application of our work, an
online decision-making portal is finally provided for decision-makers to
utilize the proposed algorithms to solve decision-making problems.Comment: Pulished by Expert Systems with Applications (ISSN: 0957-4174
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
An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and Fusion: Taxonomy and future directions
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.The reciprocal preference relation (RPR) is a powerful tool to represent decision makersâ preferences in decision making problems. In recent years, various types of RPRs have been reported and investigated, some of them being the âclassicalâ RPRs, interval-valued RPRs and hesitant RPRs. Additive consistency is one of the most commonly used property to measure the consistency of RPRs, with many methods developed to manage additive consistency of RPRs. To provide a clear perspective on additive consistency issues of RPRs, this paper reviews the consistency measurements of the different types of RPRs. Then, consistency-driven decision making and information fusion methods are also reviewed and classified into four main types: consistency improving methods; consistency-based methods to manage incomplete RPRs; consistency control in consensus decision making methods; and consistency-driven linguistic decision making methods. Finally, with respect to insights gained from prior researches, further directions for the research are proposed
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
Reconciliation, Restoration and Reconstruction of a Conflict Ridden Country
Conflict has sadly been a constant part of history. Winning a conflict and making a lasting peace are often not the same thing. While a peace treaty ends a conflict and often dictates terms from the winnersâ perspective, it may not create a lasting peace. Short of unconditional surrender, modern conflict ends with a negotiated cessation of hostilities. Such accords may have some initial reconstruction agreements, but Reconciliation, Restoration and Reconstruction (RRR) is a long term process. This study maintains that to achieve a lasting peace: 1) The culture and beliefs of the conflict nation must be continuously considered and 2) RRR is a long term effort which will occur over years not just in the immediate wake of signing a treaty or agreement. To assure the inclusion of all stakeholders and gain the best results in dealing with this âwicked problemâ, an array of Operations Research techniques can be used to support the long term planning and execution of a RRR effort. The final decisions will always be political, but the analysis provided by an OR support team will guide the decision makers to better execute consensus decisions that consider all stakeholder needs. The development of the value hierarchy framework in this dissertation is a keystone of building a rational OR supported long term plan for a successful RRR. The primary aim of the research is to propose a framework and associated set of guidelines derived from appropriate techniques of OR, Decision Analysis and Project Management (right from development of a consensus based value hierarchy to its implementation, feedback and steering corrections) that may be applied to help RRR efforts in any conflict ridden country across the globe. The framework is applicable to any conflict ridden country after incorporating changes particular to any country witnessing a prolonged conflict
A METHODOLOGY FOR THE BIDDERS EVALUATION AND SELECTION IN THE PUBLIC PROCUREMENT PROCESS BASED ON HETEROGENEOUS INFORMATION AND ADAPTIVE CONSENSUS APPROACHES
The public procurement problem is a special problem of supplier selection that requires strict adherence to the principles of non-discrimination, free competition, and transparency in the contract awarding procedures. It is a very complex multi-criteria problem, which requires the engagement of several decision-makers (experts). The public procurement problem requires the usage of different types of conflicting criteria, the combination of different models (methods and techniques) of decision-making, as well as the modeling of different forms of uncertainty, inaccuracy, and subjectivity of decision-makers, which can represent a rather complex, difficult, and lengthy decision-making process. Therefore, the paper proposes a methodology for improving the tender process that focuses on heterogeneous preference structures of information (preference ordering, utility values, fuzzy (additive) preference relations, multiplicative preference relations, and linguistic preference relations) and an adaptive consensus approach for subjectively determining the weight of criteria and evaluation and selection of alternative bids. The Simple Additive Weighting (SAW) method is used for the final ranking of bidders. The proposed methodology enables obtaining a more objective and measurable value during subjective decision-making as well as minimizing the risk of unscrupulous, incompetent, and irresponsible decision-making, which is shown in the given example
Integrating expertsâ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors
This work was supported in part by the NSF of China under grants 71171160 and 71571124, in part by the SSEM Key Research Center at Sichuan Province under grant xq15b01, in part by the FEDER funds under grant TIN2013-40658-P, and in part by Andalusian Excellence Project under grant TIC-5991.The consensus reaching process (CRP) is a dynamic and iterative process for improving the consensus level among experts in group decision making. A large number of non-cooperative behaviors exist in the CRP. For example, some experts will express their opinions dishonestly or refuse to change their opinions to further their own interests. In this study, we propose a novel consensus framework for managing non-cooperative behaviors. In the proposed framework, a self-management mechanism to generate experts' weights dynamically is presented and then integrated into the CRP. This self-management mechanism is based on multi-attribute mutual evaluation matrices (MMEMs). During the CRP, the experts can provide and update their MMEMs regarding the experts' performances (e.g., professional skill, cooperation, and fairness), and the experts' weights are dynamically derived from the MMEMs. Detailed simulation experiments and comparison analysis are presented to justify the validity of the proposed consensus framework in managing the non-cooperative behaviors.National Natural Science Foundation of China
71171160
71571124SSEM Key Research Center at Sichuan Province
xq15b01European Union (EU)
TIN2013-40658-PAndalusian Excellence Project
TIC-599
Minimum Cost Consensus Models based on Random Opinions
In some complex group decision making cases, the opinions of decision makers (DMs) present random characteristic. However, it is difficult to determine the range of opinions by knowing only their probability distributions. In this paper, we construct cost consensus models with random opinions. The objective function is obtaining the minimum consensus budget under a certain confidence level. Nonetheless, the constraints restrict the upper limit of the consensus cost, the lower limit of DMs' compensations, and the opinions deviation between DMs and the moderator. As such, probabilistic planning based on a genetic algorithm is designed to resolve the minimum cost consensus models based on China's urban demolition negotiation, which can better simulate the consensus decision-making process and obtain a satisfactory solution for the random optimization consensus models. The proposed models generalize both Ben-Arieh's minimum cost consensus model and Gong's consensus model with uncertain opinions. Considering that the opinions of DMs and the moderator obey various distributions, the models simulate the opinion characteristics more effectively. In the case analysis, a sensitivity analysis method is adopted to obtain the minimum budget, and probabilistic planning based on genetic algorithm to obtain a satisfactory solution that is closer to reality
The state of the art development of AHP (1979-2017): A literature review with a social network analysis
Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions
The state of the art development of AHP (1979-2017): a literature review with a social network analysis
Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979â1990, 1991â2001 and 2002â2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions
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