| As an important branch of economic statistics, comprehensive evaluation is increasingly attracted the attention of society and has become an effective quantitative tools in the assessment, appraisal and other activities, and its theories and methods have been widely used in many areas, such as economics, management, engineering and military.In the traditional comprehensive evaluation, the data formats are point value, which can not deal with the situations with uncertain and fuzzy information. Zadeh proposed the theory of fuzzy set, which extends the characteristic function from1or0to the membership function baluing within the closed interval [0,1]. The proposition of this theory provides us with an efficient of describing vague phenomena. It is a pity that although this theory has been widely applied in many fields of social life, it has confronted with more and more restriction and challenges as it can not covey the whole information of the object. As an extension on Zadeh’s fuzzy set, intuitionistic fuzzy set considers simultaneously such three factors, i.e., degree of membership, non-membership and hesitation, therefore, it provides more choices for describing things and is more capable of expressing uncertainty than traditional fuzzy set. More and more practical applications of intuitionistic fuzzy sets and hesitant fuzzy sets are widely applied in pattern recognition, medical diagnosis, investment decision and talents selecting and so on. With the research of intuitionistic fuzzy is more and more deep, as well as its range enlarges, research on comprehensive evaluation of intuitionistic fuzzy information is necessary and urgent. Base on this urgency, this paper thoroughly studied on comprehensive evaluation problems whose indicator values are intuitionistic fuzzy numbers. Main work includes five aspects are all listed as below:一、Study on the information aggregation approaches to intuitionistic fuzzy information. On the basis of the existed aggregation approaches of intuitionistic fuzzy set, we develop a kind of intuitionistic fuzzy dependent aggregation operator, including the intuitionistic fuzzy dependent ordered weighted averaging (IFDOWA) operator and the intuitionistic fuzzy dependent hybrid aggregation (IFDHA) operator. Some of their main properties are studied. Methods based on the IFDOWA and DIFHWA operators for multiple attribute group comprehensive evaluation are presented, respectively. Finally, two application examples are examined to show that the proposed methods are effective and practical. 二、Study on the intuitionistic fuzzy distance measures.(1) From the view of ordered weighted aggregation, we make a deep and systematic study on the intuitionistic fuzzy distance measures. We develop the intuitionistic fuzzy ordered weighted distance (IFOWD) measure. We study some of its main properties, different families and the methods for determining the IFOWD weights. Finally, we develop an application of the IFOWD to a group comprehensive evaluation with prefer information under intuitionistic fuzzy environment;(2) Based on the IFOWD, we develop the intuitionistic fuzzy hybrid weighted distance (IFHWD) measure, which can not only take the importance of given individual distances into consideration, but also emphasizes the importance of the ordered position of the given individual distances. Then we present a consensus reaching process for group comprehensive evaluation with intuitionistic fuzzy preference information based on the developed distance measures. Finally, a practical application of he developed approach to the problem of evaluating university faculty for tenure and promotion is given.三、Study on interactive group comprehensive evaluation with intuitionistic fuzzy preference relations. We discuss the basic principles and methods for interactive group comprehensive evaluation, and analyze the imitations of the general interactive group comprehensive evaluation process. Based on this, an improved interactive group comprehensive evaluation process is proposed. With respect to interactive group comprehensive evaluation with intuitionistic fuzzy preference relations, we first utilize the intuitionistic fuzzy weighted averaging operator to aggregate all individual intuitionistic fuzzy preference relations into a collective intuitionistic fuzzy preference relation. Then, based on the degree of similarity between the individual intuitionistic fuzzy preference relations and the collective one, we develop three methods to determine the experts’weights. Furthermore, based on intuitionistic fuzzy preference relations, a practical interactive procedure for group comprehensive evaluation is proposed, in which the similarity measures between the collective preference relation and intuitionistic fuzzy ideal solution are used to rank the given alternatives. Finally, an illustrative numerical example is given to verify the developed approach. Meanwhile, the characters between the other method and the algorithm are compared.四、Study on intuitionistic fuzzy comprehensive evaluation problems in which the information of weights is incomplete.(1) We present a new method to derive the weights of experts and rank the preference order of alternatives based on projection models. We first derive the weights of the decision makers according to the projection of the individual decision on the ideal decision. The expert has a large weight if his evaluation value is close to the ideal decision, and has a small weight if his evaluation value is far from the ideal decision. Then, based on the weighted projection of the alternatives on the intuitionistic fuzzy ideal solution (IFIS), we develop a straightforward and practical algorithm to rank alternatives.(2) For the special situations where the information about attribute weights is completely unknown or partially known, the minimization of whole deviation between experts’ and ideal preferences can be achieved through the establishment of programming model, by solving linear programming, the optimized criteria weight coefficients ale attained. Then, we can calculate degree of similarity between the experts’ information and the ideal one, by which the ranking of alternatives can be obtained. Finally, we apply this method to group decision making problems in which the experts’evaluation set is {good, bad, abstaining}. An illustrative example is given to demonstrate its practicality and effectiveness.Finally, the research workings and main results obtained in the dissertation are summarized, and several problems which need to be further perfected and studied are pointed in this thesis. |
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