Relative entropy evaluation method for multiple attribute decision making
Liu Bei-shang
Abstract
Liu Bei-shang
Abstract
To overcome the shortcomings of the technique for order preferenceby similarity to ideal(TOPSIS),this paper presents a new method to solve the problem in the multiple attribute decision making based on relative entropy. By using the relative entropy between an alternative and the ideal solution,and between the alternative and the negative-ideal solution,a new relative closeness to the ideal solutions is defined. Therefore,a new synthetically evaluation method-relative entropy evaluation method is developed. This method is compared with TOPSIS method,angle measure evaluation method and project method,which indicates that the relative entropy evaluation method can get good results when other methods all fail.
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To overcome the shortcomings of the technique for order preferenceby similarity to ideal(TOPSIS),this paper presents a new method to solve the problem in the multiple attribute decision making based on relative entropy. By using the relative entropy between an alternative and the ideal solution,and between the alternative and the negative-ideal solution,a new relative closeness to the ideal solutions is defined. Therefore,a new synthetically evaluation method-relative entropy evaluation method is developed. This method is compared with TOPSIS method,angle measure evaluation method and project method,which indicates that the relative entropy evaluation method can get good results when other methods all fail.
Key concepts: TOPSIS, Ideal solution, Closeness, Entropy (arrow of time), Kullback–Leibler divergence, Mathematics, Mathematical optimization, Computer science