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New Combined Weighting Model Based on Maximizing the Difference in Evaluation Results and Its Application

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  • Bin Meng
  • Guotai Chi

Abstract

This paper presents an approach for weighting indices in the comprehensive evaluation. In accordance with the principle that the entire difference of various evaluation objects is to be maximally differentiated, an adjusted weighting coefficient is introduced. Based on the idea of maximizing the difference between the adjusted evaluation scores of each evaluation object and their mean, an objective programming model is established with more obvious differentiation between evaluation scores and the combined weight coefficient determined, thereby avoiding contradictory and less distinguishable evaluation results of single weighting methods. The proposed model is demonstrated using 2,044 observations. The empirical results show that the combined weighting method has the least misjudgment probability, as well as the least error probability, when compared with four single weighting methods, namely, G1, G2, variation coefficient, and deviation methods.

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  • Bin Meng & Guotai Chi, 2015. "New Combined Weighting Model Based on Maximizing the Difference in Evaluation Results and Its Application," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, September.
    • Handle: RePEc:hin:jnlmpe:239634
    DOI: 10.1155/2015/239634
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    Cited by:

    1. Guoteng Xu & Shuai Peng & Chengjiang Li & Xia Chen, 2023. "Synergistic Evolution of China’s Green Economy and Digital Economy Based on LSTM-GM and Grey Absolute Correlation," Sustainability, MDPI, vol. 15(19), pages 1-29, September.

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