Journal
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
Volume 24, Issue 1, Pages 1-12Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S021848851650001X
Keywords
Intuitionistic fuzzy set; multi-attribute decision making; fuzzy measure; Shapley value; Choquet integral
Categories
Funding
- National Natural Science Foundation of China [61273209, 71571123]
- Natural Science Foundation of Jiangsu Province [BK20150721]
- Central University Basic Scientific Research Business Expenses Project [skgt201501]
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Intuitionistic fuzzy sets can describe the uncertainty and complexity of the world flexibly, so it has been widely used in multi-attribute decision making. Traditional intuitionistic fuzzy aggregation operators are usually based on the probability measure, namely, they consider that the attributes of objects are independent. But in actual situations, it is difficult to ensure the independence of attributes, so these operators are unsuitable in such situations. Fuzzy measure is able to depict the relationships among the attributes more comprehensively, so it can complement the traditional probability measure in dealing with the multi-attribute decision making problems. In this paper, we first analyze the existing intuitionistic fuzzy operators based on fuzzy measure, then introduce two novel additive intuitionistic fuzzy aggregation operators based on the Shapley value and the Choquet integral, respectively, and show their advantages over other ones.
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