%0 Journal Article %A Houda Abadlia and Nadia Smairi and Khaled Ghedira %D 2018 %J International Journal of Computer and Information Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 143, 2018 %T An Enhanced Particle Swarm Optimization Algorithm for Multiobjective Problems %U https://publications.waset.org/pdf/10009813 %V 143 %X Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems. %P 1010 - 1018