@article{(Open Science Index):https://publications.waset.org/pdf/10009813, title = {An Enhanced Particle Swarm Optimization Algorithm for Multiobjective Problems}, author = {Houda Abadlia and Nadia Smairi and Khaled Ghedira}, country = {}, institution = {}, abstract = {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. }, journal = {International Journal of Computer and Information Engineering}, volume = {12}, number = {11}, year = {2018}, pages = {1010 - 1018}, ee = {https://publications.waset.org/pdf/10009813}, url = {https://publications.waset.org/vol/143}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 143, 2018}, }