Hesitant Fuzzy Graph and Its Application to Multi-attribute Decision Making
ZHANG Chao, LI Deyu
1.Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education,School of Computer and Information Technology, Shanxi University, Taiyuan 030006
Abstract As an effective tool for describing indecisiveness quantitatively, hesitant fuzzy sets deal with the hesitation and the fuzziness in uncertain information simultaneously to solve multi-attribute decision making problems under the background of indecisiveness. Aiming at multi-attribute decision making problems with hesitant fuzzy attribute values, the related model and the multi-attribute decision making approach based on the fuzzy graph theory are studied. Firstly, the concept of hesitant fuzzy graph and some common operational laws are presented. Then, a general hesitant fuzzy graph-based multi-attribute decision making method is established. Finally, an illustrative example and the comparative analysis are conducted to verify the feasibility of the proposed method.
Fund:Supported by National Natural Science Foundation of China(No.61672331,61573231,61432011,U1435212,61303107,61272095), Natural Science Foundation of Shanxi Province(No.201601D021076,201601D021072,2015021101,2015091001-0102)
About author:: 张 超,男,1989年生,博士,讲师,主要研究方向为智能优化计算、粒计算.E-mail:zhch3276152@163.com. 李德玉(通讯作者),男,1965年生,博士,教授,主要研究方向为粒计算、机器学习.E-mail:lidysxu@163.com.
[1] ZADEH L A. Fuzzy Logic-A Personal Perspective. Fuzzy Sets and Systems, 2015, 281: 4-20. [2] BUSTINCE H, BARRENECHEA E, PAGOLA M, et al. A Historical Account of Types of Fuzzy Sets and Their Relationships. IEEE Transactions on Fuzzy Systems, 2015, 24(1): 179-194. [3] TORRA V. Hesitant Fuzzy Sets. International Journal of Intelligent Systems, 2010, 25(6): 529-539. [4] XIA M M, XU Z S. Hesitant Fuzzy Information Aggregation in Decision Making. International Journal of Approximate Reasoning, 2011, 52(3): 395-407. [5] CHEN N, XU Z S, XIA M M. Correlation Coefficients of Hesitant Fuzzy Sets and Their Applications to Clustering Analysis. Applied Mathematical Modelling, 2013, 37(4): 2197-2211. [6] YANG X B, SONG X N, QI Y S, et al. Constructive and Axiomatic Approaches to Hesitant Fuzzy Rough Set. Soft Computing, 2014, 18(6): 1067-1077. [7] ZHANG C, LI D Y, YAN Y. A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses. Computational and Mathematical Methods in Medicine, 2015. DOI: 10.1155/2015/292710. [8] 张小路.基于犹豫模糊信息的多属性决策方法研究.博士学位论文.南京:东南大学, 2015. (ZHANG X L. Research on Multiple Attribute Decision Making Methods with Hesitant Fuzzy Information. Ph. D Dissertation. Nanjing, China: Southeast University, 2015.) [9] 王宝丽,梁吉业,胡运红.基于粒计算的犹豫模糊多准则决策方法.模式识别与人工智能, 2016, 29(3): 252-262. (WANG B L, LIANG J Y, HU Y H. Granular Computing Based Hesitant Fuzzy Multi-criteria Decision Making. Pattern Recognition and Artificial Intelligence, 2016, 29(3): 252-262.) [10] ZHANG C, LI D Y, Mu Y M, et al. An Interval-Valued Hesitant Fuzzy Multigranulation Rough Set over Two Universes Model for Steam Turbine Fault Diagnosis. Applied Mathematical Modeling, 2017, 42: 693-704. [11] 张 超,李德玉,翟岩慧.双论域上的犹豫模糊语言多粒度粗糙集及其应用.控制与决策, 2017, 32(1): 105-110. (ZHANG C, LI D Y, ZHAI Y H. Hesitant Fuzzy Linguistic Multigranulation Rough Set over Two Universes and Its Application. Control and Decision, 2017, 32(1): 105-110.) [12] GARMENDIA L, DEL CAMPO R G, RECASENS J. Partial Or-derings for Hesitant Fuzzy Sets. International Journal of Approximate Reasoning, 2017, 84: 159-167. [13] ROSENFELD A. Fuzzy Graphs // ZADEH L A, FU K S, SHIMURA M, eds. Fuzzy Sets and Their Applications. New York, USA: Academic Press, 1975: 77-95. [14] MORDESON J N, PENG C S. Operations on Fuzzy Graphs. Information Sciences, 1994, 79(3/4): 159-170. [15] BHUTANI K R, BATTOU A. On M-strong Fuzzy Graphs. Information Sciences, 2003, 155(1/2): 103-109. [16] AKRAM M, DUDEK W A. Interval-Valued Fuzzy Graphs. Computers & Mathematics with Applications, 2011, 61(2): 289-299. [17] 杨文华,李生刚.区间值模糊图的运算性质.模糊系统与数学, 2013, 27(2): 127-135. (YANG W H, LI S G. Operation Properties of Interval-Valued Fuzzy Graphs. Fuzzy Systems and Mathematics, 2013, 27(2): 127-135.) [18] 索南仁欠,李生刚.区间值强模糊图的运算性质.计算机工程与应用, 2014, 50(17): 12-15. (SUONAN R Q, LI S G. Strong Interval Value Fuzzy Operation Properties of Graph. Computer Engineering and Applications, 2014, 50(17): 12-15.) [19] SINGH P K, KUMAR C A. Bipolar Fuzzy Graph Representation of Concept Lattice. Information Sciences, 2014, 288: 437-448. [20] DRAKOPOULOS G, GOURGARIS P, KANAVOS A, et al. A Fuzzy Graph Framework for Initializing K-means. International Journal on Artificial Intelligence Tools, 2016, 25(6): 165-186. [21] SAMANTA S, PAL M. Fuzzy Planar Graphs. IEEE Transactions on Fuzzy Systems, 2015, 23(6): 1936-1942. [22] RASHMANLOU H, SAMANTA S, PAL M, et al. Product of Bipolar Fuzzy Graphs and Their Degree. International Journal of Gene-ral Systems, 2016, 45(1). DOI: 10.1080/03081079.2015.1072521. [23] MATHEW S, MORDESON J N. Connectivity Concepts in Fuzzy Incidence Graphs. Information Sciences, 2017, 382/383: 326-333.