The estimation of the median and mean is a central problem in statistics. When it comes to permutation data the median estimation problem is called aggregation problem. The problem is challenging both computationally and statistically, since provable algorithms are known only for a hand-full of cases. In this paper, we consider the permutation aggregation problem in a general probabilistic setting. This algorithm is given a data-set drawn form a distribution P and a choose for a distance function d and outputs the provably good estimator for the median of P in polynomial time. For the first time, one algorithm can be shown to work for different generating distributions.