Notice of RetractionImproved Particle Swarm Cooperative Optimization Algorithm Based on Chaos & Simplex Method

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Based on standard particle swarm optimization, the centroid of particle swarm is introduced in particle swarm optimization to enhance inter-particle cooperation and information sharing capabilities, then combining with ergodicity of the chaotic motion and fast convergence of the simplex algorithm, an improved hybrid particle swarm cooperative optimization algorithm is proposed to improve global optimum efficiency and accuracy of particle swarm optimization algorithm. Simulation results of Benchmark functions show the new algorithm improves the local searching efficiency and global searching performance effectively, and has faster convergence speed and higher precision.