Approach for uncertain multi-attribute decision-making with interval numbers complementary preference relation on alternatives under partial weight information

摘要

The uncertain multi-attribute decision making (UMADM) problem that the information about attribute weights is known partly and the decision maker (DM) has preference information on alternatives in the form of interval numbers complementary judgment matrix is investigated. Firstly, based on interval numbers complementary matrix the objective decision information is uniformed by using a translation function and then a goal programming model is established. The attribute weights are obtained by solving the model and thus the overall values of every alternative are gained. Secondly, by using an existing priority formula of possibility the alternatives are ranked. An approach based on the goal programming model and possibility is proposed. It is characterized by simple operation and easy to implement on computer. Finally, a practical example is illustrated to show the feasibility and availability of the developed method.