基于新直觉模糊距离的随机决策方法

李鹏, 吴君民, 朱建军

系统工程理论与实践 ›› 2014, Vol. 34 ›› Issue (6) : 1517-1524.

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系统工程理论与实践 ›› 2014, Vol. 34 ›› Issue (6) : 1517-1524. DOI: 10.12011/1000-6788(2014)6-1517
论文

基于新直觉模糊距离的随机决策方法

    李鹏1, 吴君民1, 朱建军2
作者信息 +

Stochastic multi-criteria decision-making methods based on new intuitionistic fuzzy distance

    LI Peng1, WU Jun-min1, ZHU Jian-jun2
Author information +
文章历史 +

摘要

针对指标权重未知,方案的指标值为直觉模糊数的随机直觉模糊决策问题,提出了一种基于前景理论和新的直觉模糊距离的随机决策方法. 首先提出一种新的直觉模糊相似度公式,在此基础上构建了一种以直觉模糊数形式表征的直觉模糊距离公式以减少在运算中信息的丢失,运用直觉模糊熵方法确定指标权重,通过前景理论对方案进行对比和排序.最后,算例分析说明了该方法的合理性和可行性.

Abstract

For the stochastic multi-criteria decision-making problem, in which the information on criteria's weights is incomplete and the indices value of alternatives are in the form of intuitionistic fuzzy numbers, an intuitionistic fuzzy stochastic decision-making approach based on prospect theory and a new intuitionistic fuzzy distance formula is proposed. First, a new intuitionistic fuzzy similarity degree fomula was proposesd and a new intuitionistic fuzzy distance definition and formula expressed by intuitionistic fuzzy number was put forward to reduce the information miss in the calculation. Then, the weight of attributes was obtained by utilizing entropy for intuitionistic fuzzy sets. The best alternative was got by using prospect theory. Finally, an example showed the feasibility and validity of this method.

关键词

决策 / 直觉模糊数 / 直觉模糊相似度 / 前景理论 / 距离

Key words

decision making / intuitionistic fuzzy number / intuitionistic fuzzy similarity degree / prospect theory / distance

引用本文

导出引用
李鹏 , 吴君民 , 朱建军. 基于新直觉模糊距离的随机决策方法. 系统工程理论与实践, 2014, 34(6): 1517-1524 https://doi.org/10.12011/1000-6788(2014)6-1517
LI Peng , WU Jun-min , ZHU Jian-jun. Stochastic multi-criteria decision-making methods based on new intuitionistic fuzzy distance. Systems Engineering - Theory & Practice, 2014, 34(6): 1517-1524 https://doi.org/10.12011/1000-6788(2014)6-1517
中图分类号: C934   

参考文献

[1] Zadeh L A. Fuzzy sets[J]. Information and Control, 1965, 8: 338-353.
[2] Atanassov K T. Intuitionistic fuzzy sets[J]. Fuzzy Sets and Systems, 1986, 20(1): 87-96.
[3] Xu Z S. Some similarity measures of intuitionistic fuzzy sets and their applications to multiple attribute decision making[J]. Fuzzy Optimization Decision Making, 2007, 6(2): 109-121.
[4] Li D F. Multi-attribute decision making models and methods using intuitionistic fuzzy sets[J]. Journal of Computer and System Science, 2005, 70(1): 73-85.
[5] Liu H W, Wang G J. Multi-criteria decision-making methods based on intuitionistic fuzzy sets[J]. European Journal of Operations Research, 2007, 179(1): 220-233.
[6] Wu J Z, Zhang Q. Multicriteria decision making method based on intuitionistic fuzzy weighted entropy[J]. Expert Systems with Applications, 2011(1): 916-922.
[7] Wei G W. Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making[J]. Expert Systems with Applications, 2011(9): 11671-11677.
[8] 李鹏,刘思峰. 基于灰色关联分析和D-S证据理论的区间直觉模糊决策方法[J].自动化学报, 2011, 37(8): 993-998.Li Peng, Liu Sifeng. An interval-valued intuitionistic fuzzy numbers decision-making method based on grey incidence analysis and D-S theory of evidence[J]. Acta Automatica Sinica, 2011, 37(8): 993-998.
[9] 李鹏,刘思峰,方志耕. 基于灰色关联分析和MYCIN不确定因子的直觉模糊决策方法[J].控制与决策, 2011, 26(11): 1680-1684.Li Peng, Liu Sifeng, Fang Zhigeng. Intuitionistic fuzzy numbers decision-making method based on grey incidence analysis and MYCIN certainty factor[J]. Control and Decision, 2011, 26(11): 1680-1684.
[10] Chen Z P, Yang W. A new multiple attribute group decision making method in intuitionistic fuzzy setting[J]. Applied Mathematical Modelling, 2011(9): 4424-4437.
[11] Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk[J]. Econometrica, 1979, 47(2): 263-292.
[12] Rottenstreich Y, Hsee C K. Money, kisses, and electric shocks: On the affective psychology of risk[J]. Psychological Science, 2001, 12(3): 185-190.
[13] Tamura H. Behavioral models for complex decision analysis[J]. European Journal of Operational Research, 2005, 166(3): 655-665
[14] 张晓,樊治平.一种基于前景随机占优准则的随机多属性决策方法[J].控制与决策, 2010, 25(12): 1875-1879.Zhang Xiao, Fan Zhiping. Method for stochastic multiple attribute decision making based on prospect stochastic dominance rule[J]. Control and Decision, 2010, 25(12): 1875-1879.
[15] 李春好,杜元伟. 不确定环境下的两层交互式有限理性决策方法[J].系统工程理论与实践, 2010, 30(11): 2003-2012.Li Chunhao, Du Yuanwei. Interactive bounded rationally approach to two level decision making under uncertainty[J]. Systems Engineering — Theory & Practice, 2010, 30(11): 2003-2012.
[16] 王坚强, 周玲. 基于前景理论的灰色随机多准则决策方法[J]. 系统工程理论与实践, 2010, 30(9): 1658-1664.Wang Jianqiang, Zhou Ling. Grey stochastic multi-criteria decision-making approach based on prospect theory[J]. Systems Engineering — Theory & Practice, 2010, 30(9): 1658-1664.
[17] 王坚强,孙腾,陈晓红.基于前景理论的信息不完全的模糊多准则决策方法[J].控制与决策, 2009, 24(8): 1198-1202.Wang Jianqiang, Sun Teng, Chen Xiaohong. Multi-criteria fuzzy decision-making method based on prospect theory with incomplete information[J]. Control and Decision, 2009, 24(8): 1198-1202.
[18] 周维,王明哲.基于前景理论的风险决策权重研究[J]. 系统工程理论与实践, 2005, 25(2): 74-78.Zhou Wei, Wang Mingzhe. Weighting risk under uncertainty based on prospect theory[J]. Systems Engineering — Theory & Practice, 2005, 25(2): 74-78.
[19] 李春好,杜元伟,刘成明,等. 基于基元前景交叉判断的前景价值模型[J].管理科学学报, 2010, 13(2): 12-23.Li Chunhao, Du Yuanwei, Liu Chengming, et al. Prospect value model via cross judgments of basic prospects[J]. Journal of Management Sciences in China, 2010, 13(2): 12-23.
[20] 胡军华, 陈晓红, 刘咏梅.基于语言评价和前景理论的多准则决策方法[J]. 控制与决策, 2009, 24(10): 1477-1482.Hu Junhua, Chen Xiaohong, Liu Yongmei. Multi-criteria decision making method based on linguistic evaluation and prospect theory[J]. Control and Decision, 2009, 24(10): 1477-1482.
[21] Liu P D, Jin F, Zhang X, et al. Research on the multi-attribute decision-making under risk with interval probability based on prospect theory and the uncertain linguistic variables[J]. Knowledge-Based Systems, 2011(24): 554-561.
[22] 张洪美,徐泽水,陈琦.直觉模糊集的聚类方法研究[J].控制与决策, 2007, 22(8): 882-888.Zhang Hongmei, Xu Zeshui, Chen Qi. On clustering approach to intuitionistic fuzzy sets[J]. Control and Decision, 2007, 22(8): 882-888.
[23] Wang Z, Xu Z S, Liu S S, et al. A netting clustering analysis method under intuitionistic fuzzy environment[J]. Applied Soft Computing, 2011, 11(8): 5558-5564.
[24] Chen S M, Tan J M. Handling multi-criteria fuzzy decision-making problems based on vague set theory[J]. Fuzzy Sets and Systems, 1994, 67(2): 163-172.
[25] Hong D H, Choi C H. Multi-criteria fuzzy decision making problems based on vague set theory[J]. Fuzzy Sets and Systems, 2000, 144(1): 103-113.
[26] 徐泽水.直觉模糊信息集成理论及应用[M].北京:科学出版社, 2008.Xu Zeshui. Intuitionistic fuzzy information integration theory and its application[M]. Beijing: Science Press, 2008.
[27] Szmidt E, Kacprzyk J. Entropy for intuitionistic fuzzy sets[J]. Fuzzy Sets and Systems, 2001, 118(3): 467-477.
[28] 王坚强,李婧婧.基于记分函数的直觉随机多准则决策方法[J].控制与决策, 2010, 25(9): 1297-1306.Wang Jianqiang, Li Jingjing. Intuitionistic random multi-criteria decision-making approach based on score functions[J]. Control and Decision, 2010, 25(9): 1297-1306.

基金

国家自然科学基金(71171112,70701017);国家社科基金(11GBL039);教育部博士点基金(20133220120002)
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