Linguistic-stochastic multi-criterion decision-making method based on cloud model
Jian Cun Ren · Computer Integrated Manufacturing Systems · 2012
To solve the linguistic-stochastic multi-criterion decision-making problems with incomplete information,a solving method based on one-dimension normal clouds and relative satisfaction degrees was designed.In the method,uncertain linguistic evaluation labels of the alternatives under criteria were transformed into approximate one-dimension normal clouds according to the normal distribution law and the golden section ratio method.By the numerical characteristics' variation method,the clouds' distances between alternatives and ideal alternative(positive or negative)were measured under the criteria.Through the operation law of interval numbers,the weighted distances between alternatives and ideal alternative(positive or negative)were calculated.The relative satisfaction degrees of the alternatives were gotten,and the ranking order of the alternatives was defined.The urban public transportation network optimization was taken as an example to show the validity and the feasibility of proposed method.