Mobile Clustering Agents based on Differential Evolution

Searching is an important procedure in optimization problems. As is an effective clustering method especially in spatial data mining, the role of searching is essential. While many searching methods focus themselves on particle swarm optimization and genetic algorithms, we propose a new searching algorithm based differential evolution (DE). It proves that DE is a simple optimization algorithm effective for real-valued problems. A simple convergence analysis with a design of experimental model are presented.