A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decomposition

Author:

Al Moubayed Noura,Petrovski Andrei,McCall John

Publisher

Springer Berlin Heidelberg

Reference21 articles.

1. Zhang, Q., Li, H.: Moea/d: A multi-objective evolutionary algorithm based on decomposition. IEEE Trans. on Evolutionary Computation 11(6), 712–731 (2007)

2. Zhang, Q., Liu, W., Li, H.: The performance of a new version of moea/d on cec09 unconstrained mop test instances. In: CEC 2009: Proceedings of the Eleventh Conference on Congress on Evolutionary Computation, Norway, pp. 203–208. IEEE, Los Alamitos (2009)

3. Awwad Shiekh Hasan, B., Gan, J.Q., Zhang, Q.: Multi-objective evolutionary methods for channel selection in brain-computer interfaces: some preliminary experimental results. In: WCCI, Barcelona, Spain, pp. 3339–3344. IEEE, Los Alamitos (2010)

4. Wang, Z., Durst, G.L., Eberhart, R.C., Boyd, D.B., Ben Miled, Z.: Particle swarm optimization and neural network application for qsar. In: Parallel and Distributed Processing Symposium, International, vol. 10, p. 194 (2004)

5. Jaishia, B., Ren, W.: Finite element model updating based on eigenvalue and strain. Mechanical Systems and Signal Processing 21(5), 2295–2317 (2007)

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