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.