An Integrated Approach to Index Weight Based on Improved D-S Evidence Theory and Application of the Product Solution Evaluation

Abstract:

To overcome the defect of the traditional method to determine attribute weight in the multiple attribute decision making problems, this paper proposed a kind of data fusion method based on The D-S Evidence Theory improved by The Grey Correlation Analysis. The method, firstly, calculated the basic probability assignment functions discount factor based on The Grey Correlation Analysis, then let the subjective weight and objective weight together based on D-S combination rules in order to avoid the deficiency of the single weighting method. Using the fusion of evaluation indexs subjective and objective weight of mobile phone product solution as an example, the results show that the proposed method is effective.

• Periodical: Advanced Materials Research (Volumes 834-836)
• Pages: 1654-1658
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.834-836.1654
• Online since: October 2013
• Authors: Er Tian Hua, Wei Han*, Da Qiang Chen, Jian Zhang
• Keywords: D-S Evidence Theory, Grey Correlation Analysis, Multiple Attribute Decision Making, Objective Weight, Subjective Weight

References

[1] Satty T L. The Analytic Hierarchy Process. McGraw Hill Inc. NY, (1980).

[2] Mareschal B. Weight stability intervals in multi-criteriadecision [J]. European Journal of Operational Research, 1998, (33): 54-64.

[3] Zhongjun Wang. Multiobjective Weight Assigning Methods and Their Choice Strategies[J]. Systems Engineering and Electronics, 1993, 06: 35-41+34. In Chinese.

[4] Johanna M. Harte, Pieter Koele and Gijsbert van Engelenburg. Estimation of attribute weight in a multi-attribute choice situation[J]. Acta Psychological, (1996).

DOI: 10.1016/0001-6918(96)00021-2

[5] Weixian WEI, Jia Feng. Study on Multiobjective Weight Combination Assigning Method[J]. Systems Engineering and Electronics, 1998, 02: 15-17. In Chinese.

[6] F. Herrera, L. Martinez, P.J. Sanchez. Managing non-homogeneous information in group decision making[J]. European Journal of Operational Research, 2005, 166: 115-132.

DOI: 10.1016/j.ejor.2003.11.031

[7] Xindong Wu, Fanlun Xiong. A learning model for weight coefficients in multi-objective evaluation[J]. Information and Control, 1988, 06: 1-5. In Chinese.

[8] Zhiping Fan, Quan Zhang, Jian Ma. An Integrated Approach to Determining Weight in Multiple Attribute Decision Making[J]. Journal of Manegement Sciences in China, 1998, (3): 50-53. In Chinese.

[9] Zeshui Xu, Qingli Da. Study on Method of Combination Weighting[J]. Chinese Journal of Management Science, 2002, (2): 84-87. In Chinese.

[10] Xiuying Cao, Jingguo Liang. The Method of Ascertaining Attribute Weight Based on Rough Sets Theory[J]. Chinese Journal of Management Science, 2002, (5): 98-100. In Chinese.

[11] Yufeng Zhou, Fajie Wei. The Method for Determining the Posterior Weight of Expert Based on Fuzzy Judgment Matrices[J]. Chinese Journal of Management Science, 2006, (3): 71-75. In Chinese.

[12] Chuanmin Mi, Sifeng Liu, Yaoguo Dang, Zhigeng Fang. Study on grey entropy weight clustering decision-making[J]. Systems Engineering and Electronics, 2006, 28(12): 1823-1844. In Chinese.

DOI: 10.1109/wcica.2006.1713206

[13] Yanhua Fu. A Weighted Averaging Method Based on Overall Weight of Discounted Evidences[J]. Journal of Northeastern University(Natural Science), 2010, 07: 917-920. In Chinese.

[14] Jie Cui, Yaoguo Dang, Sifeng Liu. An Improved Approach for Determining Weight of Attributes in Decision Making Based on Grey incidence[J]. Chinese Journal of Management Science, 2008, 05: 141-145. In Chinese.

[15] Yanbin Du, Huajun Cao, Fei Liu, Ping Yan, LI Congbo. Evaluation of machine tool remanufacturing scheme based on entropy weight and AHP[J]. Computer Integrated Manufacturing Systems, 2011, 17(1): 84-88. In Chinese.