ABSTRACT
A permutation is a list that orders objects or candidates with a preference function or
a criterion. Some examples include results from a search engine on the internet, athlete
rankings, lists of genes related to a disease given by prediction methods or simply the
preference of activities for the next weekend. One might be interested to aggregate a set
of permutations to get a consensus permutation. This problem is well known in political
science and many methods exists that can aggregate permutations, each one having its
mathematical properties. Among those methods, the Kemeny-Young method, also known
as the median of permutations, finds a consensus that minimise the sum of distances
between that consensus and the set of permutations. This method holds many desirable
properties. On the other end, this method is difficult to calculate, thus opening the way
for research works. A generalization of this problem considers rankings containing ties
between the ranked objects and rankings that might be incomplete by considering only
a subset of objects. In this thesis, we study the Kemeny-Young method under different
aspects :
— Firstly, a search space reduction technique is proposed. It improves the time com-
plexity of exact algorithms for the problem.
— Secondly, a well parameterized heuristic is developed and is used as guidance in
a branch-and-bound exact algorithm. This algorithm also uses a new search space
reduction technique.
— Thirdly, the special case of the problem on three permutations is investigated. A
search space reduction technique based on graphs is presented for this case, followed
by a very tight lower bound. Two conjectures are stated and are linking this case
with the 3-Hitting Set problem.
— Finally, a generalization of the problem is proposed and allows us to extend our
work on search space reduction techniques to the rank aggregation problem.
Key words : Kemeny-Young method, median of permutations, Kemeny’s rule,
Kendall-τdistance, rank aggregation, ranking’s consensus, preferential votes,
voting system, rankings, permutations, optimization, algorithms
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