Sequential rank aggregation method

Rank aggregation is a fundamental technique of different application domains. In this paper, we propose a new rank aggregation method. This method models the rank aggregation problem as an assignment problem and solves it by integer programming, where the objective function is set to minimize the sum of the squared Euclidean Distance between each initial ranking and the aggregated ranking. To avoid the computational limitation in working with large datasets, a sequential aggregation approach has been adopted. This approach proceeds sequentially in several steps. In each step, only two rankings are aggregated. It thus reduces the computational limitation of the proposed method. An illustration of the proposed method using datasets of green car adoption in Taiwan is presented in this paper. The results show that the proposed method can solve the rank aggregation problem effectively and efficiently.