A fast and elitist multi-objective particle swarm algorithm: NSPSO
Yang Liu · 2008
In this paper, a new nondominated sorting particle swarm optimisation (NSPSO), is proposed, that combines the operations (fast ranking of non-dominated solutions, crowding distance ranking and elitist strategy of combining parent population and offspring population together) of a known MOGA NSGA-II and the other advanced operations (selection and mutation operations) with a single particle swarm optimiser (PSO). The efficacy of this algorithm is demonstrated on 2 test functions, and the comparison is made with the NSGA-II and a multi-objective PSO (MOPSO-CD). The simulation results suggest that the proposed optimisation framework is able to achieve good solutions as well diversity compared to NSGA-II and MOPSO-CD optimisation framework.