The purpose of this paper is to propose a grey target decision model based on cobweb area in order to overcome the effect and influence from the extreme value of the index on the decision result. However, it does not take into account the impact of the correlation between indicators on the angle of the index, and produce a certain degree decision information distortion as a result of the equal angle between the indicators. In order to solve the above problems, a novel grey decision-making model based on cone volume is proposed.
In this paper, the model uses the whitening weight function to whiten the interval grey number, and the Delphi method and the maximal entropy method are exploited to integrate the weight of the index. On the basis of this, the center of the bull’s eye, the weight and the index value are constructed as the center circle, the radius, and the high cone, respectively. The scheme is selected by the volume of the cone, the decision is made according to the order relation, and the example is utilized to prove and analyze the validity of the proposed model.
The results show that the proposed model can well improve the traditional grey target decision-making model from the modeling object and modeling method.
The method exposed in the paper can be used to deal with the grey target decision-making problems which characteristics are multi-indexes, and the attribute values are interval grey numbers.
The paper succeeds in overcoming the disadvantages of grey target decision making based on the target center distance and the cobweb area.
This work is partially funded by the National Natural Science Foundation of China (No. 71503103); Natural Science Foundation of Jiangsu Province (No. BK20150157); Social Science Foundation of Jiangsu Province (No. 14GLC008); the Fundamental Research Funds for the Central Universities (No. 2017JDZD06).
Wang, L. and Qian, W. (2017), "Grey target decision-making model of interval grey number based on cone volume", Grey Systems: Theory and Application, Vol. 7 No. 2, pp. 247-258. https://doi.org/10.1108/GS-04-2017-0010Download as .RIS
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