• DocumentCode
    2962959
  • Title

    Stochastic rough normal distribution multi-criteria decision-making method based on SRN-WAA operator

  • Author

    Yang Zhi-hai ; Chen Yan ; Li Tao-Ying ; Li Peng-hui

  • Author_Institution
    Sch. of Transp. Manage. Coll., Dalian Maritime Univ., Dalian, China
  • fYear
    2013
  • fDate
    17-19 July 2013
  • Firstpage
    458
  • Lastpage
    462
  • Abstract
    This paper investigates a multiple attribute decision making problem, whose attribute values are stochastic rough normal distribution. We define stochastic rough normal distribution variables, and then propose rules and stochastic rough normal distribution aggregation operator (SRN-WAA). The method based on SRN-WAA operator is proposed for the problem of the incomplete information on attribute´s weights and it´s values in terms of random variables. In order to confirm the optimal criterion weights, we use the attribute´s variance and attribute´s weights which obey normal distribution to establish optimization. And it uses SRN-WAA operator to integrate criterion for obtaining the alternative´s evaluation of estimate. Besides it receives the sequencing of the mean of alternatives by means of comparing composite evaluation. Finally, a numerical example shows the effectiveness of the proposed method.
  • Keywords
    decision making; random processes; statistical distributions; stochastic processes; SRN-WAA operator; aggregation operator; attribute value; attribute variance; attribute weight; multicriteria decision-making; multiple attribute decision making; optimal criterion weights; random variable; stochastic rough normal distribution; Approximation methods; Decision making; Educational institutions; Gaussian distribution; Programming; Set theory; Stochastic processes; SRN-WAA operator; alternative ranking; decision-making; multi-criteria; stochastic rough normal distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering (ICMSE), 2013 International Conference on
  • Conference_Location
    Harbin
  • ISSN
    2155-1847
  • Print_ISBN
    978-1-4799-0473-0
  • Type

    conf

  • DOI
    10.1109/ICMSE.2013.6586321
  • Filename
    6586321