Modelling Heterogeneity among Experts in Multi-criteria Group Decision Making Problems

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dc.contributor.author Perez, IJ
dc.contributor.author Alonso, S
dc.contributor.author Cabrerizo, F
dc.contributor.author Lu, J
dc.contributor.author Herrera-Viedma, E
dc.contributor.editor al, VTE
dc.date.accessioned 2012-10-12T03:36:19Z
dc.date.issued 2011-01
dc.identifier.citation Lecture Notes in Computer Science: Proceedings of the 8th International Conference, Modeling Decisions for Artificial Intelligence MDAI 2011, 2011, pp. 55 - 66
dc.identifier.isbn 978-3-642-22588-8
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/19179
dc.description.abstract Heterogeneity in group decision making problems has been recently studied in the literature. Some instances of these studies include the use of heterogeneous preference representation structures, heterogeneous preference representation domains and heterogeneous importance degrees. On this last heterogeneity level, the importance degrees are associated to the experts regardless of what is being assessed by them, and these degrees are fixed through the problem. However, there are some situations in which the experts importance degrees do not depend only on the expert. Sometimes we can find sets of heterogeneously specialized experts, that is, experts whose knowledge level is higher on some alternatives and criteria than it is on any others. Consequently, their importance degree should be established in accordance with what is being assessed. Thus, there is still a gap on heterogeneous group decision making frameworks to be studied. We propose a new fuzzy linguistic multi-criteria group decision making model which considers different importance degrees for each expert depending not only on the alternatives but also on the criterion which is taken into account to evaluate them.
dc.format Scott McWhirter
dc.publisher Springer
dc.relation.isbasedon 10.1007/978-3-642-22589-5_7
dc.title Modelling Heterogeneity among Experts in Multi-criteria Group Decision Making Problems
dc.type Conference Proceeding
dc.parent Lecture Notes in Computer Science: Proceedings of the 8th International Conference, Modeling Decisions for Artificial Intelligence MDAI 2011
dc.journal.number en_US
dc.publocation The Netherlands en_US
dc.identifier.startpage 55 en_US
dc.identifier.endpage 66 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 001038
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity 20110728 en_US
dc.date.activity 2011-07-28
dc.location.activity Changsha, China en_US
dc.description.keywords Group decision making ? multi-criteria decision making ? heterogeneous decision frameworks ? linguistic approach en_US
dc.description.keywords Pattern-Classification
dc.description.keywords Instance Selection
dc.description.keywords Algorithms
dc.description.keywords Search
dc.description.keywords Group decision making multi-criteria decision making heterogeneous decision frameworks linguistic approach
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)
utslib.collection.history Uncategorised (ID: 363)


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