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IJML 2012 Vol.2(1): 46-51
doi: 10.7763/IJMLC.2012.V2.88

An Approach towards Enterprise Architecture Analysis using AHP and Fuzzy AHP

M. Razavi Davoudi1 , K. Sheikhvand1,2

  • 1Islamic Azad University, Central Tehran Branch, Poonak, Tehran, Iran.
  • 2Politecnico di Milano, Milan, Italy

Abstract

Enterprise Architecture (EA) as a discipline that manages large amount of models and information about different aspects of the enterprise can support decision making on enterprise-wide issues. In order to provide such support, EA information should be amenable to analysis of various utilities and quality attributes. In this regard, this paper provides an approach based on Fuzzy Analytical Hierarchy Process (AHP) towards EA analysis. It proposes an extended quantitative method of assessing quality attribute achievement of different scenarios using AHP and Fuzzy AHP based on the knowledge and experience of EA experts and domain experts. Due to the uncertainty in the judgments of participants, the crisp pair-wise comparison in the conventional AHP is insufficient and imprecise to capture the right judgments. Therefore, a fuzzy logic is introduced in the pair-wise comparison of AHP in one of steps of the method. The applicability of the proposed approach is demonstrated using a practical case study.

Keywords

  • Enterprise architecture analysis
  • quality attribute
  • analytical hierarchy process
  • fuzzy logic
  • fuzzy AHP
88-A890

How to Cite

Copied

M. Razavi Davoudi and K. Sheikhvand, "An Approach towards Enterprise Architecture Analysis using AHP and Fuzzy AHP," International Journal of Machine Learning, vol. 2, no. 1, pp. 46-51, 2012. https://doi.org/10.7763/IJMLC.2012.V2.88

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD