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2008 International Conference on Computational Intelligence and Security
A Novel Multi-Objective Evolutionary Algorithm Based on External Dominated Clustering
December 13-December 17
ISBN: 978-0-7695-3508-1
Evolutionary algorithms (EAs) have wide applications in practice and many advantages over traditional methods in solving nonlinear and complex optimal problems. In this paper, we propose a novel clustering technique, in which the infeasible solutions are employed to divide the feasible solutions into several clusters. There is no more one infeasible individual in each cluster. A novel evolutionary algorithm based on this technique called ED-MOEA is proposed for dealing with constrained multi-objective problems. Simulation results on five test problems indicate the proposed algorithm is effective.
Citation:
Lei Fan, Yuping Wang, "A Novel Multi-Objective Evolutionary Algorithm Based on External Dominated Clustering," cis, vol. 1, pp.162-167, 2008 International Conference on Computational Intelligence and Security, 2008
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