基于加权BF-TOPSIS的多属性决策方法研究

Research on multi-attribute decision making method based on weighted BF-TOPSIS

BF-TOPSIS算法结合置信方程和TOPSIS算法,能够有效处理多属性决策问题。加权BF-TOPSIS(WBFTOPSIS)算法是对BF-TOPSIS算法的有效推广,保留了BF-TOPSIS算法的优越性。文章首先对BF-TOPSIS算法的归一化问题进行详细推理分析,并给出BBAs构造的一种新的证明。通过分析BF-TOPSIS算法BBAs构造的实际意义,提出WBF-TOPSIS算法,并给出加权系数的最优化表达式。BF-TOPSIS算法是WBF-TOPSIS算法的一种特殊情况。相比于BF-TOPSIS算法,WBF-TOPSIS算法能够做出更优的决策结果;最后算例分析验证了所提算法处理多属性决策问题的优越性性。

The BF-TOPSIS algorithm combines the belief function and the TOPSIS algorithm and can effectively deal with multi-Criteria decision-making problems. The weighted BF-TOPSIS(WBF-TOPSIS)algorithm is an effective extension of the BF-TOPSIS algorithm, and retains the superiority of the BF-TOPSIS algorithm. Firstly, this paper makes a detailed reasoning analysis on the normalization problem of the BF-TOPSIS algorithm, and gives a new proof of BBAs construction. Through the analysis of the practical significance of BBAs structure in BF-TOPSIS algorithm, the new WBF-TOPSIS algorithm is proposed and given the optimization expression of the weighting coefficient. BF-TOPSIS algorithm is a special case of the WBF-TOPSIS algorithm. Compared with BF-TOPSIS algorithm, WBF-TOPSIS algorithm can make better decision results. Finally, the example analysis verifies the superiority of the proposed algorithm to deal with multi-criteria decision-making problems.