• DocumentCode
    2852442
  • Title

    Simplification of decision making matrix in fuzzy multiple attribute decision making

  • Author

    Pei, Zhi ; Zheng, Li

  • Author_Institution
    Dept. of Ind. Eng., Zhejiang Univ. of Technol., Hangzhou, China
  • fYear
    2011
  • fDate
    6-9 Dec. 2011
  • Firstpage
    36
  • Lastpage
    40
  • Abstract
    In the multiple attribute decision making, the computational intensity of problems quickly increases with the number of attributes increases. In this paper, we will introduce the simplification theory and technology of decision matrix in fuzzy multiple attribute decision making, and propose an attribute reduction algorithm. The purpose of this algorithm is to find all of the simplest order-preserving attribute subsets and the order-preserving attribute core of the corresponding multiple attribute decision making problem. One of the simplest order-preserving attribute subsets will be exploited as a substitute of the original attribute set. Thus the original multiple attribute decision making problem could be simplified and unnecessary cost related to redundant attributes could be saved. Finally, an illustrative numerical example is given to demonstrate our approach. And through this example, a dissimilarity between the attribute reduction in decision making and the knowledge reduction in rough set theory is discovered.
  • Keywords
    decision making; fuzzy set theory; matrix algebra; rough set theory; attribute reduction algorithm; decision making matrix; fuzzy multiple attribute decision making; knowledge reduction; order-preserving attribute subsets; rough set theory; simplification theory; Decision making; Delta modulation; Engines; Fuzzy sets; Workstations; Attribute reduction; Decision making matrix; Fuzzy multiple attribute decision making; TOPSIS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on
  • Conference_Location
    Singapore
  • ISSN
    2157-3611
  • Print_ISBN
    978-1-4577-0740-7
  • Electronic_ISBN
    2157-3611
  • Type

    conf

  • DOI
    10.1109/IEEM.2011.6117874
  • Filename
    6117874