Begin with the disjoint clustering having level L(0) = 0 and sequence number m = 0.
    Find the least dissimilar pair of clusters in the current clustering, say pair (r), (s), according to

    d[(r),(s)] = min d[(i),(j)]

    where the minimum is over all pairs of clusters in the current clustering.
    Increment the sequence number : m = m +1. Merge clusters (r) and (s) into a single cluster to form the next clustering m. Set the level of this clustering to

    L(m) = d[(r),(s)]
    Update the proximity matrix, D, by deleting the rows and columns corresponding to clusters (r) and (s) and adding a row and column corresponding to the newly formed cluster. The proximity between the new cluster, denoted (r,s) and old cluster (k) is defined in this way:

    d[(k), (r,s)] = min d[(k),(r)], d[(k),(s)]
    If all objects are in one cluster, stop. Else, go to step 2.