  We review the background of the cluster algorithms in Monte Carlo simulation
of statistical physics problems. One of the first such successful algorithm was
developed by Swendsen and Wang eight years ago. In contrast to the local
algorithms, cluster algorithms update dynamical variables in a global fashion.
Therefore, large changes are made in a single step. The method is very
efficient, especially near the critical point of a second-order phase
transition. Studies of various statistical mechanics models and some
generalizations of the algorithm will be briefly reviewed. We mention
applications in other fields, especially in imaging processing.
