An application of particle swarm optimization algorithm to clustering analysis

• DOI: 10.1007/s00500-009-0539-5
• Publication Date: 2009-12-15T07:07:01Z
• Authors: R. J. Kuo; M. J. Wang; T. W. Huang
• Keywords: Centroid

Particle swarm optimization algorithm (PSOA), which maintains a population of particles, where each particle represents a potential solution to an optimization problem, is a population-based stochastic search process. This study intends to integrate PSOA with K-means to cluster data. It is shown that PSOA can be employed to find the centroids of a user-specified number of clusters. The proposed PSOA is evaluated using four data sets, and compared to the performance of some other PSOA-based methods and K-means method. Computational results show that the proposed method has much potential. A real-world problem for order clustering also illustrates that the proposed method is quite promising.