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The Research of Determining Weights Method for Multiple Attribute Group Decision Making Based on Multi-granularity Two-tuple Linguistic Information

Author: WangXiao
Tutor: ChenHuaYou
School: Anhui University
Course: Operational Research and Cybernetics
Keywords: Multi-granularity Tuple linguistic Relative entropy Projection Deviation TOPSIS Combination Weighting
CLC: C934
Type: Master's thesis
Year: 2010
Downloads: 182
Quote: 0
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Abstract


Affected by the complexity of the objective things, uncertainty and vagueness of human thinking and other factors, the actual decision-making information is often difficult to quantify, and generally a better choice to represent the qualitative form of the language. In group decision making, due to different decision-makers of the same decision-making problems according to their personal preferences put forward a number of different language phrases (size) language evaluation set given each linguistic assessment information, and therefore multi-granularity linguistic assessment information group decision-making problems has high practical value. In this paper, for the decision-making information tuple linguistic form of multi-granularity multi-attribute group decision making, to determine the weight goal programming model to get the attribute weights and decision-making, the main work is summarized as follows: the first chapter, first introduced the multi-granularity binary semantic background information of multi-attribute group decision making research and research status, Finally, the main research work. Chapter II, multi-granularity linguistic information used the binary semantic information in the form and use conversion functions to achieve consistent evaluation information, were established based on the relative entropy and projection-based multi-objective planning on binary semantic information in Weights The objective attribute weights completely conditions determine the decision-making problems, and finally the use of the tuple linguistic aggregation operators to assemble information on various programs and program merit. Chapter interval language information for multi-granularity interval binary semantic information in the form and use conversion functions to achieve consistent evaluation information were established based on the maximizing deviation based on Topsis the tuple linguistic information about the range of target planning and, respectively, in the right weight information completely unknown and not completely unknown the conditions, to determine the decision problem of the objective attributes the right weight, and last, respectively, the use of interval two yuan semantics possible degree formula and between the programs and the positive ideal program is relatively close to the degree of the various programs of the information to assemble and merit-based. Chapter comprehensive subjective weighting method and objective weighting method, the properties of multi-attribute group decision-making problems in multi-granularity linguistic information right weight combination weighting proposed a combination resulting from the sum of squares combination weighting method, weight. Chapter V, through the case study of the first three chapters of the four objective weighting methods and combination weighting method, these methods are effective and feasible. Chapter VI, the full text of the summary, and prospected further research prospects.

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