A novel ecological-biological-behavior praticle swarm optimization for Ackley´s function

Basing on the simulation of a social metaphor instead of the survival of the fittest individual paradigm, particle swarm optimization is a population-based swarm intelligence algorithm. Inspired by the conventional particle swarm method, ecological theory, and biological theory, this work proposes a novel ecological-biological-behaved particle swarm optimization (EBB-PSO) algorithm using logical growth model with symbiotic relationship. The simulation results demonstrate good performance of the proposed algorithm in solving a significant benchmark problem in multi-modal function, namely the Ackley´s problem.