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Performance assessment of DMOEA-DD with CEC 2009 MOEA competition test instances

Published: 18 May 2009 Publication History

Abstract

In this paper, the DMOEA-DD, which is an improvement of DMOEA[1, 2] by using domain decomposition technique, is applied to tackle the CEC 2009 MOEA competition test instances that are multiobjective optimization problems (MOPs) with complicated Pareto set (PS) geometry shapes. The performance assessment is given by using IGD [3, 4] as performance metric.

References

[1]
X. Zou, Y. Chen, M. Liu and L. Kang, "A New Evolutionary Algorithm for Solving Many-objective Optimization Problems", IEEE Trans. on System, Man and Cybernetics, Part B, vol. 38, pp. 1402-1412, 2008.
[2]
X. Zou, M. Liu, L. Kang, and J. He, "A high performance multi-objective evolutionary algorithm based on the principles of thermodynamics", in Proc. Parallel Problem Solving from Nature 8th Int. Conf., vol. 3242, LNCS, X. Yao, E. Burke, J.A. Lozano, J. Smith, J.J. Merelo-Guervòs, J.A. Bullinaria, J. Rowe, P. Tino, A. Kabán, and H.-P. Schwefel, Eds., Berlin, Germany: Springer-Verlag, Sep. 2004, pp. 922-931.
[3]
H. Li and Q. Zhang, "Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D and NSGAII," IEEE Trans. Evol. Comp., Accepted, 2008.
[4]
A. Zhou, Q. Zhang and Y. Jin, "Approximating the Set of Pareto Optimal Solutions in Both the Decision and Objective Spaces by an Estimation of Distribution Algorithm," Working Report CES-485, Dept of CES, University of Essex, 06/2008.
[5]
Q. Zhang and H. Li, "MOEA/D: A Multi-objective Evolutionary Algorithm Based on Decomposition, IEEE Trans. on Evolutionary Computation", vol. 11, no. 6, pp. 712-731, 2007.
[6]
Z. Yang, K. Tang and X. Yao, "Differential Evolution For High-Dimensional Function Optimization," Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, pp. 3523-3530, 25-28 Sept. 2007.
[7]
Q. Zhang, A. Zhou, S. Zhao, P. N. Suganthan, W. Liu, and S. Tiwari, "Multiobjective optimization test instances for the CEC 2009 special session and competition," University of Essex and Nanyang Technological University, Tech. Rep. CES-487, 2008.
[8]
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multi-objective genetic algorithm: NSGA-II," IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.

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Published In

cover image Guide Proceedings
CEC'09: Proceedings of the Eleventh conference on Congress on Evolutionary Computation
May 2009
3356 pages
ISBN:9781424429585

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IEEE Press

Publication History

Published: 18 May 2009

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  • (2012)Adaptive multi-objective genetic algorithm using multi-pareto-rankingProceedings of the 14th annual conference on Genetic and evolutionary computation10.1145/2330163.2330228(449-456)Online publication date: 7-Jul-2012
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