Multivariate dynamic comprehensive evaluation method with reward and punishment function and its application

被引:0
作者
Yi, Ping-Tao [1 ]
Zhou, Ying [1 ]
Guo, Ya-Jun [1 ]
机构
[1] School of Business Administration, Northeastern University
来源
Dongbei Daxue Xuebao/Journal of Northeastern University | 2014年 / 35卷 / 04期
关键词
Comprehensive evaluation; Dynamic evaluation; Modificatory factor; Modificatory function; Variation coefficient;
D O I
10.3969/j.issn.1005-3026.2014.04.032
中图分类号
O24 [计算数学];
学科分类号
070102 ;
摘要
For the multivariate dynamic evaluation problem of reward and punishment, a multivariate dynamic comprehensive correction method was put forward to conduct the horizontal and vertical correction by using modificatory factor and modificatory function. And the evaluation result with disciplinary action was gained. Based on this, corresponding variation coefficient according to the changes of correction value was formulated, so that the evaluated object and its index performance in the entirety were gotten. In addition, the adjustment factors of proportion of rewards and punishments" and "performance pay" can be set by the variation coefficient size. A final example showed the validity of the proposed method. This method is suitable for practical and complex problems such as talent screening and performance evaluation even more."
引用
收藏
页码:597 / 599+608
相关论文
共 11 条
[1]  
Yi P.-T., Multi-source Information Density Rally Operator Theory and Application, pp. 158-165, (2012)
[2]  
Herrera F., Herrera-Viedma E., Chiclana F., Militiaperson decision-making based on multiplicative preference relations, European Journal of Operational Research, 129, 2, pp. 372-385, (2001)
[3]  
Liu X.W., Some properties of the weighted OWA operator, IEEE Transactions on Systems, Man, and Cybernetics, 36, 1, pp. 118-127, (2006)
[4]  
George W.R.G., Nonlinear decision weights in choice under uncertainty, Management Science, 45, 1, pp. 74-85, (1999)
[5]  
Yager R.R., Induced ordered weight averaging operators, IEEE Transaction on Systems, Man, and Cybernetics, 29, 2, pp. 141-150, (1999)
[6]  
Sung T.K., Chang N., Lee G., Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction, Journal of Management Information Systems, 16, 1, pp. 63-85, (1999)
[7]  
Xu X.Z., A note on the subjective and objective integrated approach to determine attribute weights, European Journal of Operational Research, 156, 2, pp. 530-532, (2004)
[8]  
Xu Z.S., Da Q.L., An overview of operators for aggregating information, International Journal of Intelligent Systems, 18, 9, pp. 953-969, (2003)
[9]  
Xu Z.S., A method based on linguistic aggregation operators for group decision making with linguistic preference relations, Information Sciences, 166, 1-4, pp. 19-30, (2004)
[10]  
Yi P.-T., Guo Y.-J., Zhang D.-N., A multi-phase information aggregation method based on extensive inspiriting control lines, Operation Research and Management Science, 19, 1, pp. 49-55, (2010)