Advertisement

Fuzzy Multi-Attribute Decision Making Using an Information Axiom-Based Approach

  • Cengiz Kahraman
  • Osman Kulak
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 16)

Abstract

Axiomatic design (AD) provides a framework to describe design objects and a set of axioms to evaluate relations between intended functions and the means by which they are achieved. Since AD has the characteristics of multi-attribute evaluation, it is proposed for multi-attribute comparison of some alternatives. The comparison of these alternatives is made for the cases of both complete and incomplete information. The crisp AD approach for complete information and the fuzzy AD approach for incomplete information are developed. In this chapter, the numeric applications of both crisp and fuzzy AD approaches for the comparison of flexible-manufacturing systems are given.

Key words

Axiomatic design multi-attribute information axiom flexible manufacturing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Büyüközkan, G., Ertay, T., Kahraman, C., and Ruan, D., 2004, Determining the importance weights for the design requirements in the house of quality using the fuzzy analytic network approach, International Journal of Intelligent Systems, 19(5): 443-461.zbMATHCrossRefGoogle Scholar
  2. De Boer, L., Van Der Wegen, L., and Jan Telgen, J., 1998, Outranking methods in support of supplier selection, European Journal of Purchasing and Supply Management, 4(2-3): 109-118.CrossRefGoogle Scholar
  3. Deng, H., Yeh, C.H., and Willis, R.J., 2000, Inter-company comparison using modified TOPSIS with objective weights, Computers & Operations Research, 27: 963-973.zbMATHCrossRefGoogle Scholar
  4. Hartley, R.V.L., 1928, Transmission of information, The Bell Systems Technical Journal, 7: 535-563.Google Scholar
  5. Kahraman, C., Cebeci, U., and Ruan, D., 2004, Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey, International Journal of Production Economics, 87: 171-184.CrossRefGoogle Scholar
  6. Kulak, O., and Kahraman, C., 2005, Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design, International Journal of Production Economics, 95: 415-424CrossRefGoogle Scholar
  7. Kulak, O., Durmusoglu, M.B., and Kahraman, C., 2005, Multi-attribute equipment selection based on information axiom, Journal of Materials Processing Technology, 169: 337-345.CrossRefGoogle Scholar
  8. Nelson, C.A., 1986, A scoring model for flexible manufacturing systems project selection, European Journal of Operational Research, 24: 346-359.CrossRefGoogle Scholar
  9. Shannon, C.E., 1948, The mathematical theory of communication, The Bell System Technical Journal, 27: 379-423.zbMATHMathSciNetGoogle Scholar
  10. Suh, N.P., 2001, Axiomatic Design: Advances and Applications, Oxford University Press, New York.Google Scholar
  11. Suh, N.P., 1995, Design and operation of large systems, Annals of CIRP, 14(3): 203-213.Google Scholar
  12. Suh, N.P., 1990, The Principles of Design, Oxford University Press, New York.Google Scholar
  13. Zadeh, L.A., 1965, Fuzzy sets, Information and Control, 8: 338-353.zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2008

Authors and Affiliations

  • Cengiz Kahraman
    • 1
  • Osman Kulak
    • 2
  1. 1.Industrial Engineering DepartmentIstanbul Technical UniversityMacka, IstanbulTurkey
  2. 2.Industrial Engineering DepartmentPamukkale UniversityDenizliTurkey

Personalised recommendations