Predictive mathematical model for solving multi-criteria decision-making problems
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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.
KeywordsTOPSIS Ranking Objective Subjective Comprehensive Rank sum Grey relational Mean square weight method
This work forms part of the R and D activities of TIFAC-CORE in Automotive Infotronics located at VIT University, Vellore. The authors would like to thank DST, Government of India, for providing necessary hardware and software support for completing this work successfully.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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