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Analytical Hierarchy Process under Group Decision Making with Some Induced Aggregation Operators

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014)

Abstract

This paper focuses on the extension of Analytical Hierarchy Process under Group Decision Making (AHP-GDM) with some induced aggregation operators. This extension generalizes the aggregation process used in AHP-GDM by allowing more flexibility in the specific problem under consideration. The Induced Ordered Weighted Average (IOWA) operator is a promising tool for decision making with the ability to reflect the complex attitudinal character of decision makers. The Maximum Entropy OWA (MEOWA) which is based on the maximum entropy principle and the level of ‘orness’ is a systematic way to derive weights for decision analysis. In this paper, the focus is given on the integration of some induced aggregation operators with the AHP-GDM based-MEOWA as an extension model. An illustrative example is presented to show the results obtained with different types of aggregation operators.

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Yusoff, B., Merigó Lindahl, J.M. (2014). Analytical Hierarchy Process under Group Decision Making with Some Induced Aggregation Operators. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_49

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  • DOI: https://doi.org/10.1007/978-3-319-08795-5_49

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08794-8

  • Online ISBN: 978-3-319-08795-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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