An Intelligent Particle Swarm Optimization (IPSO) for MO problems is proposed based on AER (Agent-Environment-Rules) model, in which Competition and Clonal Selection operator are designed to provide an appropriate selection pressure to propel the swarm population towards the Pareto-optimal front. Simulations and comparison with NSGA-II and MOPSO indicate that IPSO is highly competitive.
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- Improving PSO-Based Multiobjective Optimization Using Competition and Immunity Clonal
- Springer Berlin Heidelberg