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Journal article Open Access

A Method under Uncertain Information for the Selection of Students in Interdisciplinary Studies

José M. Merigó; Pilar López-Jurado; M.Carmen Gracia; Montserrat Casanovas

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<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.1084480</identifier>
      <creatorName>José M. Merigó</creatorName>
      <creatorName>Pilar López-Jurado</creatorName>
      <creatorName>M.Carmen Gracia</creatorName>
      <creatorName>Montserrat Casanovas</creatorName>
    <title>A Method under Uncertain Information for the Selection of Students in Interdisciplinary Studies</title>
    <subject>Decision making</subject>
    <subject>Selection of students</subject>
    <subject>Aggregation operators.</subject>
    <date dateType="Issued">2009-07-22</date>
  <resourceType resourceTypeGeneral="JournalArticle"/>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1084480</alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1084479</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/waset</relatedIdentifier>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">We present a method for the selection of students
in interdisciplinary studies based on the hybrid averaging
operator. We assume that the available information given in
the problem is uncertain so it is necessary to use interval
numbers. Therefore, we suggest a new type of hybrid
aggregation called uncertain induced generalized hybrid
averaging (UIGHA) operator. It is an aggregation operator
that considers the weighted average (WA) and the ordered
weighted averaging (OWA) operator in the same formulation.
Therefore, we are able to consider the degree of optimism of
the decision maker and grades of importance in the same
approach. By using interval numbers, we are able to represent
the information considering the best and worst possible results
so the decision maker gets a more complete view of the
decision problem. We develop an illustrative example of the
proposed scheme in the selection of students in
interdisciplinary studies. We see that with the use of the
UIGHA operator we get a more complete representation of the
selection problem. Then, the decision maker is able to
consider a wide range of alternatives depending on his
interests. We also show other potential applications that could
be used by using the UIGHA operator in educational problems
about selection of different types of resources such as
students, professors, etc.</description>
    <description descriptionType="Other">{"references": ["G. Beliakov, A. Pradera, and T. Calvo, Aggregation Functions: A guide\nfor practitioners, Springer-Verlag, Berlin, 2007.", "J.M. Merig\u251c\u2502, New Extensions to the OWA Operators and its application\nin decision making, PhD Thesis (in Spanish), Dept. Business\nAdministration, Univ. Barcelona, Barcelona, Spain, 2008.", "J.M. Merig\u251c\u2502, and M. Casanovas, \"Induced aggregation operators in\ndecision making with Dempster-Shafer belief structure\", Int. J.\nIntelligent Systems (to be published).", "J.M. Merig\u251c\u2502, M. Casanovas, \"The induced generalized hybrid averaging\noperator and its application in financial decision making\", International Journal of Business, Economics, Finance and Management Sciences\n(submitted for publication).", "J.M. Merig\u251c\u2502, M. Casanovas, \"Uncertain decision making with\nDempster-Shafer theory\", In Proceedings of the IPMU International\nConference, Torremolinos - M\u251c\u00edlaga, Spain, 2008, pp. 425-432.", "J.M. Merig\u251c\u2502, and A.M. Gil-Lafuente, \"The induced generalized OWA\noperator\", Information Sciences, vol. 179, pp. 729-741, 2009.", "Z.S. Xu, \"A Note on Linguistic Hybrid Arithmetic Averaging Operator\nin Multiple Attribute Group Decision Making with Linguistic\nInformation\", Group Decision and Negotiation, vol. 15, pp. 593-604,\n2006.", "Z.S. Xu, \"An approach based on the uncertain LOWG and induced\nuncertain LOWG operators to group decision making with uncertain\nmultiplicative linguistic preference relations\", Decision Support Systems,\nvol. 41, pp. 488-499, 2006.", "R.R. Yager, and J. Kacprzyck, The Ordered Weighted Averaging\nOperators: Theory and Applications, Kluwer Academic Publishers,\nNorwell, MA, 1997.\n[10] R.R. Yager, \"On Ordered Weighted Averaging Aggregation Operators\nin Multi-Criteria Decision Making\", IEEE Trans. Systems, Man and\nCybernetics, vol. 18, pp. 183-190, 1988.\n[11] Z.S. Xu, and Q.L. Da, \"An Overview of Operators for Aggregating\nInformation\", Int. J. Intelligent Systems, vol. 18, pp. 953-969, 2003.\n[12] R.R. Yager, and D.P. Filev, \"Induced ordered weighted averaging\noperators\", IEEE Trans. Syst. Man Cybern., vol. 29, pp. 141-150, 1999.\n[13] Z.S. Xu, and Q.L. Da, \"The Uncertain OWA Operator\", Int. J. Intelligent\nSystems, vol. 17, pp. 569-575, 2002.\n[14] N. Karayiannis, \"Soft Learning Vector Quantization and Clustering\nAlgorithms Based on Ordered Weighted Aggregation Operators\", IEEE\nTrans. Neural Networks, vol. 11, 1093-1105, 2000.\n[15] R.R. Yager, \"Generalized OWA Aggregation Operators\", Fuzzy Opt.\nDecision Making, vol. 3, pp.93-107, 2004.\n[16] G. Beliakov, \"Learning Weights in the Generalized OWA Operators\",\nFuzzy Opt. Decision Making, vol. 4, pp. 119-130, 2005.\n[17] T. Calvo, G. Mayor, and R. Mesiar, Aggregation Operators: New Trends\nand applications, Physica-Verlag, New York, 2002.\n[18] J. Fodor, J.L. Marichal, and M. Roubens, \"Characterization of the\nordered weighted averaging operators\", IEEE Trans. Fuzzy Systems, vol.\n3, pp. 236-240, 1995.\n[19] J.M. Merig\u251c\u2502, and M. Casanovas, \"The fuzzy generalized OWA\noperator\", In Proceedings of the Conference SIGEF 2007, pp. 504-517,\nPoiana-Brasov, Romania, 2007.\n[20] J.M. Merig\u251c\u2502, M. Casanovas, \"The uncertain generalized OWA operator\nand its application in the selection of financial strategies\", In\nProceedings of the International Conference AEDEM 2007, pp. 547-\n556, Krakow, Poland, 2007.\n[21] J.H. Wang, and J. Hao, \"A new version of 2-tuple fuzzy linguistic\nrepresentation model for computing with words\", IEEE Trans. Fuzzy\nSystems, vol. 14, pp. 435-445, 2006.\n[22] P.A. Schaefer, and H.B. Mitchell, \"A generalized OWA operator\", Int. J.\nIntelligent Systems, vol. 14, pp. 123-143, 1999.\n[23] Z.S. Xu, \"A method based on linguistic aggregation operators for group\ndecision making with linguistic preference relations\", Information\nSciences, vol. 166, pp. 19-30, 2004.\n[24] R.R. Yager, \"On generalized measures of realization in uncertain\nenvironments\", Theory and Decision, vol. 33, pp. 41-69, 1992.\n[25] R.R. Yager, \"Families of OWA operators\", Fuzzy Sets and Systems, vol.\n59, pp. 125-148, 1993.\n[26] R.R. Yager, \"Quantifier Guided Aggregation Using OWA operators\",\nInt. J. Intelligent Systems, vol. 11, pp. 49-73, 1996.\n[27] R.R. Yager, E-Z OWA weights, In Proceedings of the 10th International\nFuzzy Systems Association (IFSA) World Congress, Istanbul, Turkey, pp.\n39-42, 2003.\n[28] R.R. Yager, \"Induced aggregation operators\", Fuzzy Sets and Systems,\nvol. 137, pp. 59-69, 2003.\n[29] R.R. Yager, \"Centered OWA operators\", Soft Computing, vol. 11, pp.\n631-639, 2007.\n[30] R.R. Yager, and D.P. Filev, \"Parameterized \"andlike\" and \"orlike\"\nOWA operators\", Int. J. General Systems, vol. 22, pp. 297-316, 1994.\n[31] R. Moore, Interval analysis, Prentice-Hall, Englewood Cliffs, NJ, 1966."]}</description>
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