Predictive mathematical model for solving multi-criteria decision-making problems

被引:0
作者
N. Deepa
K. Ganesan
Balaji Sethuramasamyraja
机构
[1] VIT University,School of Information Technology and Engineering
[2] VIT University,School of Information Technology and Engineering
[3] California State University,Department of Industrial Technology, Jordan College of Agricultural Sciences and Technology
来源
Neural Computing and Applications | 2019年 / 31卷
关键词
TOPSIS; Ranking; Objective; Subjective; Comprehensive; Rank sum; Grey relational; Mean square weight method;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, a predictive mathematical model is proposed to identify the best alternatives from the given set of alternatives characterized by multiple criteria. An objective function is developed to find the ranking index of the alternatives. A new Comprehensive-Technique for Order Preference by Similarity to Ideal Solution (C-TOPSIS) method is proposed which combines the comprehensive weights of the criteria with TOPSIS method. The proposed predictive mathematical model generates a ranking of the alternatives. An experimental study has been carried out by taking agricultural data set of rice paddy crop to demonstrate and validate the developed model. The results show significant correlation between the ranks obtained by the proposed model and the ranks obtained from the average yield per hectare. Also the results of the proposed method outperform the results of the other ranking methods, namely VIKOR and ELECTRE, particularly in the real world example. Thus, the developed predictive mathematical model seems to provide better results for the given alternatives and can also be used for other decision-making problems.
引用
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页码:6733 / 6746
页数:13
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