Local search and hybrid diversity strategy based multi-objective particle swarm optimization algorithm
Heng Yue · Kongzhi yu juece · 2012
In order to improve the convergence and diversity performance,a local search and hybrid diversity strategy based multi-objective particle swarm optimization algorithm(LH-MOPSO) is proposed.LH-MOPSO makes full use of the augmented Lagrange multiplier method to approach the Pareto optimal solutions quickly,and the hybrid diversity strategy based on modified Maximin fitness function and crowding distance is used for maintaining the diversity of nondominated solutions.Meanwhile,Gaussian mutation operator is introduced to avoid LH-MOPSO premature convergence.Finally,an efficient constraint handling method is proposed.Simulation results show that LH-MOPSO has good performance.