The method of interval multi-attribute decision-making based on cross entropy

This paper presents a new method to solve the problem in the interval multiple attribute decision making based on cross entropy. By using the cross entropy between an alternative (which will be evaluated) and the ideal solution between the alternative and the negative-ideal solution, we define a new relative closeness to the ideal solutions. And the priority is given by the closeness. This method can avoid comparing and ranking interval numbers and effectively keep the information of the interval number. By comparison with other methods of multiple attribute decision making based on distance, we concluded that the proposed method can used to rank when other methods all fail.