An interactive ranking-based multi-criteria choice algorithm with filtering: Applications to university selection

In this study, we develop an interactive algorithm to converge to the most preferred alternative of a decision maker (DM) among a set of discrete alternatives. The algorithm presents a limited number of alternatives to the DM and collects preference ranking of them iteratively. The preferences are modeled by a flexible and realistic preference function. To improve the performance, the alternatives presented are determined by a filtering method. We compare our algorithm with benchmark algorithms on numerous data sets from Quacquarelli Symonds, a higher education marketing company that reports annual rankings of universities under different categories. The results show that our algorithm outperforms the benchmark algorithms.Publisher's Versio