@techreport{escidoc:1819193,
TITLE = {Rank-maximal through maximum weight matchings},
AUTHOR = {Michail, Dimitrios},
LANGUAGE = {eng},
URL = {http://domino.mpi-inf.mpg.de/internet/reports.nsf/NumberView/2005-1-001},
NUMBER = {MPI-I-2005-1-001},
INSTITUTION = {Max-Planck-Institut f{\"u}r Informatik},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2005},
DATE = {2005},
ABSTRACT = {Given a bipartite graph $G( V, E)$, $ V = A \disjointcup B$ where $|V|=n, |E|=m$ and a partition of the edge set into $r \le m$ disjoint subsets $E = E_1 \disjointcup E_2 \disjointcup \dots \disjointcup E_r$, which are called ranks, the {\em rank-maximal matching} problem is to find a matching $M$ of $G$ such that $|M \cap E_1|$ is maximized and given that $|M \cap E_2|$, and so on. Such a problem arises as an optimization criteria over a possible assignment of a set of applicants to a set of posts. The matching represents the assignment and the ranks on the edges correspond to a ranking on the posts submitted by the applicants. The rank-maximal matching problem has been previously studied where a $O( r \sqrt n m )$ time and linear space algorithm~\cite{IKMMP} was presented. In this paper we present a new simpler algorithm which matches the running time and space complexity of the above algorithm. The new algorithm is based on a different approach, by exploiting that the rank-maximal matching problem can be reduced to a maximum weight matching problem where the weight of an edge of rank $i$ is $2^{ \ceil{\log n} (r-i)}$. By exploiting that these edge weights are steeply distributed we design a scaling algorithm which scales by a factor of $n$ in each phase. We also show that in each phase one maximum cardinality computation is sufficient to get a new optimal solution. This algorithm answers an open question raised on the same paper on whether the reduction to the maximum-weight matching problem can help us derive an efficient algorithm.},
TYPE = {Research Report / Max-Planck-Institut für Informatik},
}