A genetic algorithm that exchanges neighboring centers for k-means clustering

We present a genetic algorithm for selecting centers to seed the popular k-means method for clustering. Using a novel crossover operator that exchanges neighboring centers, our GA identifies superior partitions using both benchmark and large simulated data sets.