Artificial Prey-Predator (APP): An efficient approach for numerical function optimization

An Artificial Prey and Predator swarm intelligence based approach motivated by the defense and attack mechanism of prey and predators is presented here. The proposed approach works in two phases i.e., prey phase and predator phase. The very design of the proposed approach has the capability to avoid the local optima with fast convergence which is evident from the simulation results carried out on the 13 benchmark test functions. The performance analysis demonstrates that the proposed Artificial Prey-Predator approach has outperformed many well-known swarm intelligence based optimization techniques.