權(quán)重信息完全未知的二維二元語義多屬性群決策方法

摘要： 針對群決策問題中專家權(quán)重和屬性權(quán)重均未知的情形,提出一種基于二維二元語義表示模型的多屬性群決策方法.首先,考慮到不同決策者對二維二元語義信息中第一維信息和第二維信息的相對重要性比重不同,提出一種能夠反映出該比重變化對于二維二元語義間比較和距離測度影響的得分函數(shù)和距離公式;其次,利用得分函數(shù)和距離公式建立目標(biāo)函數(shù),依據(jù)專家意見的熵值確立約束條件,進(jìn)而構(gòu)建能夠同時求解出專家權(quán)重和屬性權(quán)重的雙權(quán)重求解模型,再分別針對不同的方案依次進(jìn)行求解,得到每一個方案假定為最優(yōu)方案時相應(yīng)的權(quán)重信息;再次,按照所提出的新方法,綜合目標(biāo)函數(shù)值的大小對方案進(jìn)行排序與擇優(yōu);最后,通過案例分析與對比驗證所提方法的有效性和科學(xué)性.
Aiming at the situation that the weights of decision makers and criteria are both unknown in group decision making progress, we propose a liner method of multi-attribute decision making based on 2-dimension 2-tuple linguistic representation model. Considering the relative importance of the first dimensional information and the second dimensional information of 2-dimension 2-tuple linguistic information, the score function and distance measures, which can reflect the impact of the change of the proportion of the relative importance on the score function for comparing two 2-dimension2-tuple linguistic information and distance measures between them, are proposed. Then, decision makers' weight and criteria weight are solved simultaneously by constructing a model that the objective function is set up based on the score function and distance measures, and constraint conditions are established based on the entropy value of decision makers.Furthermore, the corresponding weights information which makes each alternative optimal is obtained by solving different models, then the optimal alternative and rank alternatives are chosen according to the value of the objective function.Finally, the case analysis and comparison verify the effectiveness and scientificalness of the proposed method.