A distributed data clustering based on multiple colonies swarm-like agent

This paper presents a data clustering algorithm based on the natural behaviors of social insects in multiple colonies and multiple food sources concept; agents from each colony take a food back to their colony aimed to group the food. The proposed algorithm is a distributed data clustering algorithm based on multiple swarm-like agent colonies. Its advantages are a distributed data clustering and heterogeneous dataset clustering. Simulations are conducted to illustrate its effectiveness performance for data clustering. Iris dataset and Wisconsin Breast Cancer Database (WBCD) are applied to present its efficiency.