Multi-objective PSO based on infeasibility degree and principle of endocrine

For multi-objective optimization problems with constraint,a new Particle Swarm Optimization(PSO) algorithm for multi-objective with constraint was proposed.In the method,the constraints and the selection for elite swarm were disposed by infeasibility degree and domain principle.According to the control and supervised principle between Simulation Hormone(SH) and Releasing Hormone(RH) in endocrine system,and considering the supervision and control of individual in the non-dominated set for the nearest class of swarm,the global optimization position of class was used to generate the new position for particles.In order to verify the effectiveness of the given method,two benchmark multi-objective problems were simulated by the given method,NSGA-II and MOPSO-CD.The results indicate that the given method can find feasible Pareto solutions with a large probability.