We study the problem of computing a leximin-optimal solution of a
constraint network. This problem is highly motivated by fairness and
efficiency requirements in many real-world applications implying human
agents. We compare several generic algorithms which solve this problem
in a constraint programming framework. The second one is entirely
original, and the other ones are partially based on existing works
adapted to fit with this problem. These algorithms are tested on
combinatorial auctions instances.