Combinatorial particle swarm optimization (CPSO) for partitional clustering problem

This paper presents a new clustering approach based on the combinatorial particle swarm optimization (CPSO) algorithm. Each particle is represented as a string of length n (where n is the number of data points) the ith element of the string denotes the group number assigned to object i. An integer vector corresponds to a candidate solution to the clustering problem. A swarm of particles are initiated and fly through the solution space for targeting the optimal solution. To verify the efficiency of the proposed CPSO algorithm, comparisons with a genetic algorithm are performed. Computational results show that the proposed CPSO algorithm is very competitive and outperforms the genetic algorithm.