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The Research On The Methods Of Combination Weighting And Topsis In The Multiple Attribute Decision Making

Posted on:2017-09-20Degree:MasterType:Thesis
Country:ChinaCandidate:S J FengFull Text:PDF
GTID:2349330503468174Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Multiple attribute decision making as a kind of typical group decision making problems, which mainly resolves the problem of sorting and optimal for limited schemes with multiple attributes. In the process of multiple attribute decision making, the attribute weight reflects the relative importance of attributes, it directly affects the result of the decision, therefore determining the attribute weights reasonablely are consistently one of the core of the multiple attribute decision making problem. About the determination of weight,subjective weighting method may have subjective arbitrariness and also be affected by the decision makers with lack of knowledge or experience; Objective weighting method ignore the decision makers’ subjective information; The algorithm complexity of combination method is higher, these three methods have their advantages and disadvantages. Based on the product sort of the individual user and the product evaluation of multiple users, two angles respectively determine the attribute weights and sensitivity analysis was carried out,and it is a new attempt for the attribute weights.Multiple attribute decision making method has been widely used in many fields, the deep research on multiple attribute decision making method has important meaning for solving practical problems, the TOPSIS(Technique for Order Preference by Similarity to Ideal Solution) method has intuitive geometric meaning and wide range of application,which is an effective method for multiple attribute decision making. However, with the development of the society, people encountered the multiple attribute decision making problems more and more and more complex, the traditional TOPSIS method has shown an unavailability, such as its reverse and contradictory problems. Although scholars were improved, but need to be further research.This paper discusses some problems of multiple attribute decision making, there are several research emphases in this paper:(1)In order to highlight the advantages of the method in this paper, according to the satisfaction of commodity attribute level to determine the relative importance of attributes,and based on considering the correlation between the key attribute and other attribute to confirm goods attribute weights comprehensively. Finally, examples show the effectiveness and practicality of this method.(2)This paper tries to improve the determination of attribute weights based on objective data of the user participate in the evaluation and product attributes, through improving the standardization of data matrix and determining the absolute ideal points to eliminate the rank reversal in traditional TOPSIS method. The example based on the improved TOPSIS is applied to the different brand mobile phone comprehensive evaluation shows that the improved TOPSIS evaluation method has certain validity and feasibility.(3)This article has carried on the sensitivity analysis of combination method firstly,determining the weight allow the change of scope under the condition of the two ranking remains unchanged; Secondly introducing the sensitivity analysis of attribute weights in the TOPSIS method. Finally, examples show the effectiveness of the stable interval.Multiple attribute decision making is an important part of modern decision science,which has been widely used in many fields of theory and practical application background.In recent decades, research on the problem of multiple attribute decision making has aroused people’s great attention, and has achieved fruitful results. Multiple attribute decision making, however, no matter in theory or method is still faced with new challenges,especially the study of decision making method has yet to be further improved.
Keywords/Search Tags:multiple attribute decision making, index weight, TOPSIS, sensitivity analysis
PDF Full Text Request
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