Particle swarm optimization based on endocrine regulation mechanism
Yong Hu · Control theory & applications · 2007
Motivated by high-level regulation principle of endocrine system, a particle swarm optimization based on endocrine regulation mechanism is put forward. First, emotional evaluation method is designed combining with the best fitness, average fitness and local fitness of particles in current generation, and emotion in next generation is evaluated. Then, the behaviors of particles in next generation are updated by interaction of neural and endocrine systems, and momentum factor is used to reduce the probability of local convergence. The convergence of algorithm is analyzed, and the effectiveness is demonstrated by optimization experiments of typical functions and path planning.