PIU: risk-sensitive decision making using Pareto optimization of interval utilities induced by fuzzy preference relations

被引:6
|
作者
Runkler, Thomas A. [1 ]
机构
[1] Siemens AG, Otto Hahn Ring 6, D-81739 Munich, Germany
关键词
Decision making; Fuzzy preference relations; Interval type-2 fuzzy sets; LOGIC SYSTEMS; SELECTION; MODEL;
D O I
10.1007/s00500-021-06414-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Decision making is a process that ranks or chooses subsets from given sets of options, for example, project proposals or machine tools, with high relevance in industry and economics. Each decision option may be associated with a degree of utility with respect to a specific criterion. Often experts are not willing or able to quantify utilities but rather compare individual pairs of options, which leads to fuzzy pairwise preference matrices. Conventionally, decision making on preference matrices uses scoring indices that exhibit different characteristics. Selecting the most appropriate scoring index is often difficult. Scoring indices are associated with different levels of risk, and none of these indices alone can be considered superior. We show that any fuzzy preference matrix induces interval utilities which can be interpreted as memberships of interval type-2 fuzzy sets, so preference-based decision making has to take into account uncertainty and therefore has to be risk sensitive. We propose a risk-sensitive preference-based decision making method called Pareto optimization of interval utilities (PIU) that chooses a subset of options ranked by degrees of risk. This allows the decision maker to choose an option that represents an appropriate trade-off between opportunity and risk for the given decision problem. Experiments with the YouTube Comedy Slam data set show that PIU compared with conventional scoring methods allows to trade a slight decrease in the best-case utility for a strong increase in the worst-case utility, and vice versa.
引用
收藏
页码:1 / 11
页数:11
相关论文
共 38 条
  • [31] Multi-expert multi-criteria decision making based on the likelihoods of interval type-2 trapezoidal fuzzy preference relations
    Hendiani, Sepehr
    Jiang, Lisheng
    Sharifi, Ebrahim
    Liao, Huchang
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2020, 11 (12) : 2719 - 2741
  • [32] A group decision-making method considering both the group consensus and multiplicative consistency of interval-valued intuitionistic fuzzy preference relations
    Wan, Shuping
    Wang, Feng
    Dong, Jiuying
    INFORMATION SCIENCES, 2018, 466 : 109 - 128
  • [33] Consensus-Based Multi-Person Decision Making with Incomplete Fuzzy Preference Relations Using Product Transitivity
    Rehman, Atiq-ur
    Hussain, Mustanser
    Farooq, Adeel
    Akram, Muhammad
    MATHEMATICS, 2019, 7 (02)
  • [34] A NEW METHOD FOR GROUP DECISION MAKING USING INCOMPLETE FUZZY PREFERENCE RELATIONS BASED ON THE ADDITIVE CONSISTENCY AND THE ORDER CONSISTENCY
    Chen, Shyi-Ming
    Lin, Tsung-En
    Lee, Li-Wei
    PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS (ICMLC), VOLS 1-4, 2013, : 1256 - 1261
  • [35] A shape similarity-based ranking method of hesitant fuzzy linguistic preference relations using discrete fuzzy number for group decision making
    Zhao, Meng
    Liu, Meng-Ying
    Su, Jia
    Liu, Ting
    SOFT COMPUTING, 2019, 23 (24) : 13569 - 13589
  • [36] Biobjective Optimization Method for Large-Scale Group Decision Making Based on Hesitant Fuzzy Linguistic Preference Relations With Granularity Levels
    Zheng, Yuanhang
    Xu, Zeshui
    Li, Yufei
    Pedrycz, Witold
    Yi, Zhang
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2024, 32 (08) : 4759 - 4771
  • [37] Group decision-making based on multiplicative consistency and consensus of linguistic interval-valued q-rung orthopair fuzzy preference relations
    Li, Tao
    Zhang, Liyuan
    COMPUTATIONAL & APPLIED MATHEMATICS, 2025, 44 (01):
  • [38] Incomplete interval type-2 fuzzy preference relations based on a multi-criteria group decision-making model for the evaluation of wastewater treatment technologies
    Yao, Liming
    Xu, Zhongwen
    Lv, Chengwei
    Hashim, Muhammad
    MEASUREMENT, 2020, 151