Abstract: In classical single criterion group evaluation methods, the ratings that experts (the subject) have given for the object evaluated are usually exact data. In addition, the evaluation process is also generally dominated by the subject with lack of the object participation. However, the ratings given are human judgements including preferences that may be vague; using interval data should be more suitable. Otherwise, with the circumstance of emphasizing democracy and freedom, participation of the object (especially when the object is human) in evaluation process is rather essential. Therefore, a group evaluation method based on collaboration of subject and object is put forward under interval information. In this paper, an Interval Induced Density Weighted Algorithm-IIDWA is presented to aggregate interval data. Firstly, completeness of subject information-μand integrity of object information-ωare calculated, by which original interval data are clustered into right group. Secondly, ultimate weight vector of each group are synthesized by their attribute weight vector-ξ^? and scale weight vector-ξ^e, so it will possess the superiority of containing the characteristics of attribute and scale of each group. Finally, information of subject and object are aggregated respectively by IIDWAto obtain interval comprehensive results and then possibility degree approach of interval data is conducted for ranking. In the end, a numerical example is given to illustrate the feasibility and validity of this paper. Meanwhile, the result based on the TOPSIS method with interval data is also calculated in order to compare the existing difference with ranking of this paper. As the result of the two methods show, the ranking is different, which indicates that participation of the object can make contribution to the ranking result. In this paper, the complementation of the subject and object information has been implementated.

Key words: interval information, group evaluation, IIDWA operator, subject and object, collaboration