Validation of methods for ranking fuzzy numbers in decision making

被引:1
作者
Gegov, Alexander [1 ]
Abu Bakar, Ahmad Syafadhli [1 ]
机构
[1] Univ Portsmouth, Sch Comp, Portsmouth PO1 3HE, Hants, England
关键词
Ranking; fuzzy numbers; type-1 fuzzy numbers; type-2 fuzzy numbers; Z-numbers; ranking properties; consistency; efficiency; SELECTION; HEIGHTS;
D O I
10.3233/IFS-151717
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The concept of ranking fuzzy numbers has attracted significant attention recently due to its successful use in decision making problems. This concept allows decision makers to appropriately exercise their subjective judgment under situations that are vague, imprecise, ambiguous and uncertain in nature. The literature on ranking fuzzy numbers describes the validation of ranking methods as the most important aspect of the application of these methods. This is due to the fact that the validation confirms the suitability of the associated methods for ranking fuzzy numbers and decision making purposes. In this paper, a comprehensive review on validation techniques for methods of ranking fuzzy numbers is presented. These techniques are associated with properties of ranking fuzzy quantities as well as consistency and efficiency evaluation of ranking operations. The techniques are described in detail and discussed in the context of many established and more recent works in the field.
引用
收藏
页码:1139 / 1149
页数:11
相关论文
共 50 条
  • [41] Group decision making based on hesitant fuzzy ranking of hesitant fuzzy preference relations
    Sindhu, M. Sarwar
    Rashid, Tabasam
    Khan, M.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2019, 37 (02) : 2563 - 2573
  • [42] A method of ranking interval numbers based on degrees for multiple attribute decision making
    Ye, Yicheng
    Yao, Nan
    Wang, Qiaozhi
    Wang, Qihu
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2016, 30 (01) : 211 - 221
  • [43] Multi-attribute decision making with generalized fuzzy numbers
    Li, Guangxu
    Kou, Gang
    Lin, Changsheng
    Xu, Liang
    Liao, Yi
    JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2015, 66 (11) : 1793 - 1803
  • [44] Ranking of Z-numbers based on value and ambiguity at levels of decision making
    Chutia, Rituparna
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2021, 36 (01) : 313 - 331
  • [45] Fuzzy filtering ranking method for multi-criteria decision making
    Chang, Ting-Yu
    Ku, Cooper Cheng-Yuan
    COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 156
  • [46] Ranking the sustainability performance of pavements: An intuitionistic fuzzy decision making method
    Kucukvar, Murat
    Gumus, Serkan
    Egilmez, Gokhan
    Tatari, Omer
    AUTOMATION IN CONSTRUCTION, 2014, 40 : 33 - 43
  • [47] Ranking fuzzy numbers using fuzzy maximizing-minimizing points
    Salahshour, S.
    Abbasbandy, S.
    Allahviranloo, T.
    PROCEEDINGS OF THE 7TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT-2011) AND LFA-2011, 2011, : 763 - 769
  • [48] Comparing and ranking fuzzy numbers using ideal solutions
    Deng, Hepu
    APPLIED MATHEMATICAL MODELLING, 2014, 38 (5-6) : 1638 - 1646
  • [49] Ranking of fuzzy numbers based on alpha-distance
    Khezerloo, S.
    Allahviranloo, T.
    Khezerloo, M.
    PROCEEDINGS OF THE 7TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT-2011) AND LFA-2011, 2011, : 770 - 777
  • [50] Ranking function of two LR-fuzzy numbers
    Firozja, M. Adabitabar
    Agheli, B.
    Hosseinzadeh, M.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2014, 26 (03) : 1137 - 1142