Fuzzy Engineering Economics with Applications

  • Editors
  • Cengiz Kahraman

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 233)

Table of contents

  1. Front Matter
  2. Aleksandar Dimitrovski, Manuel Matos
    Pages 11-41
  3. Cengiz Kahraman, İhsan Kaya
    Pages 71-81
  4. Manuel Matos, Aleksandar Dimitrovski
    Pages 83-95
  5. P. Sewastjanow, L. Dymowa
    Pages 105-128
  6. Cengiz Kahraman, İhsan Kaya
    Pages 129-143
  7. Cengiz Kahraman, Murat Levent Demircan
    Pages 145-157
  8. Cengiz Kahraman, İhsan Kaya
    Pages 159-171
  9. Cengiz Kahraman, Tufan Demirel, Nihan Demirel
    Pages 173-182
  10. Toshihiro Kaino, Kaoru Hirota, Witold Pedrycz
    Pages 183-216
  11. Cengiz Kahraman
    Pages 231-242
  12. Francisco Araque, Alberto Salguero, Ramon Carrasco, Luis Martinez
    Pages 289-306
  13. James J. Buckley, Esfandiar Eslami
    Pages 339-357
  14. Esra Bas, Cengiz Kahraman
    Pages 359-380
  15. Cengiz Kahraman
    Pages 381-382
  16. Back Matter

About this book


Fuzzy set approaches are suitable to use when the modeling of human knowledge is necessary and when human evaluations are needed. Fuzzy set theory is recognized as an important problem modeling and solution technique. It has been studied extensively over the past 40 years. Most of the early interest in fuzzy set theory pertained to representing uncertainty in human cognitive processes. Fuzzy set theory is now applied to problems in engineering, business, medical and related health sciences, and the natural sciences. This book handles the fuzzy cases of classical engineering economics topics. It contains 15 original research and application chapters including different topics of fuzzy engineering economics. This book will provide a useful resource of ideas, techniques, and methods for present and further research in the applications of fuzzy sets in engineering economics.


Engineering Economics calculus data mining decision support decision support system decision tree fuzziness fuzzy fuzzy set fuzzy sets knowledge modeling optimization probability uncertainty

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-540-70809-4
  • Online ISBN 978-3-540-70810-0
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site