  In this paper, we introduce an agent-based model for coalition formation
which is suitable for our usecase. We propose here two clearing-houses
mechanisms that return sound matchings. The first aims at maximizing the global
satisfaction of the individuals. The second ensures that all individuals are
assigned as much as possible to a preferred activity. Our experiments show that
the outcome of our algorithms are better than those obtained with the classical
search/optimization techniques. Moreover, their distribution speeds up their
runtime.
