Ranking Alternatives Offline Bachelor ’ s thesis

Rank aggregation describes how one can derive a consensus from multiple preferences over a given set of alternatives. Alternatives could be candidates in an election, search results ranked by search engines or businesses which are ranked by users with services like Yelp3. There are different paradigms for how the consensus should be constructed. In this thesis we will concern ourselves with the well known Kemeny and Slater rules and the FLAP4 rule. As it is NP-hard to compute the consensus with these paradigms there has been much research on producing good heuristics to decrease computation time. We will introduce and evaluate different heuristics for the different paradigms. www.yelp.com Feedback Linear Arrangement Problem