Entropy And Similarity Measure Of Intuitionistic Fuzzy Sets And Their Applications

This thesis deals with entropy and similarity measure of intuitionistic fuzzysets and their applications in intuitionistic fuzzy multi-attribute group decisionmaking problem. It consists of four chapters.In the first chapter, we introduce the origin and current research situations ofentropy, similarity measure and intuitionistic fuzzy multi-attribute group decisionmaking problem. Then we list the main achievements of this paper.In chapter2, we discuss entropy measure of intuitionistic fuzzy sets. Weclassify and compare some existing entropy measures for intuitionistic fuzzy setsaccording to whether they measure both fuzziness and intuitionism or not. Bysome numerical examples, we analyze their advantages and shortcomings. Wethen propose two new entropy measures and present their reasonability by study-ing their properties and comparing them with others.In chapter3, we research on similarity measure of intuitionistic fuzzy sets.By the relationship between entropy and similarity measure, we establish threenew similarity measures for intuitionistic fuzzy sets according to entropy measuresof intuitionistic fuzzy sets. We then compare them with some existing similaritymeasures to demonstrate their efectuality and reasonability.In the last chapter, we investigate applications of entropy and similaritymeasure in intuitionstic fuzzy multi-attribute group decision making problem. Wedetermine the weights of experts according to the uncertainty of experts’ decisionresults, the similarity degree between assessments provided by the individualexperts and the similarity degree between individual expert’s opinion and others’.Finally, we establish a multi-attribute group decision making method based on entropy and similarity measure and adopt illustrative example to demonstrate itsrationality.