Deterministic and randomized local search algorithms for clustering

We propose a local search algorithm for clustering based on deterministic variants of cluster swapping. Within a given time limit, the new method finds the correct clustering more efficiently than existing ones. The algorithm is simple to implement, which makes it useful for practitioners.