%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