Effectiveness of Entropy Weight Method in Decision-Making

Zhu Yuxin; Tian Dazuo; Yan Feng

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Effectiveness of Entropy Weight Method in Decision-Making

机译：Effectiveness of Entropy Weight Method in Decision-Making

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Entropy weight method (EWM) is a commonly used weighting method that measures value dispersion in decision-making. The greater the degree of dispersion, the greater the degree of differentiation, and more information can be derived. Meanwhile, higher weight should be given to the index, and vice versa. This study shows that the rationality of the EWM in decision-making is questionable. One example is water source site selection, which is generated by Monte Carlo Simulation. First, too many zero values result in the standardization result of the EWM being prone to distortion. Subsequently, this outcome will lead to immense index weight with low actual differentiation degree. Second, in multi-index decision-making involving classification, the classification degree can accurately reflect the information amount of the index. However, the EWM only considers the numerical discrimination degree of the index and ignores rank discrimination. These two shortcomings indicate that the EWM cannot correctly reflect the importance of the index weight, thus resulting in distorted decision-making results.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2020年第9期|3564835.1-3564835.5|共5页
作者
Zhu Yuxin; Tian Dazuo; Yan Feng;
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Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China|Nanchang Univ, Sch Civil Engn & Architecture, Nanchang 330031, Jiangxi, Peoples R China;

Hunan Inst Water Resources & Hydropower Res, Changsha 410007, Peoples R China;

Nanchang Univ, Sch Civil Engn & Architecture, Nanchang 330031, Jiangxi, Peoples R China;

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Effectiveness of Entropy Weight Method in Decision-Making

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