Fuzzy multi-criteria decision-making approach with incomplete information based on evidential reasoning

The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems. For those problems, an approach based on evidential reasoning is proposed, in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning, and then nonlinear programming models of each alternative are developed with the incomplete information on weights. The genetic algorithm is employed to solve the models, producing the weights and the utility interval of each alternative, and the ranking of the whole set of alternatives can be attained. Finally, an example shows the effectiveness of the method.