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Published in:
2005 | OriginalPaper | Chapter
An Efficient Multi-objective Evolutionary Algorithm: OMOEA-II
Authors : Sanyou Zeng, Shuzhen Yao, Lishan Kang, Yong Liu
Published in: Evolutionary Multi-Criterion Optimization
Publisher: Springer Berlin Heidelberg
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An improved orthogonal multi-objective evolutionary algorithm (OMOEA), called OMOEA-II, is proposed in this paper. Two new crossovers used in OMOEA-II are orthogonal crossover and linear crossover. By using these two crossover operators, only small orthogonal array rather than large orthogonal array is needed for exploiting optimal in the global space. Such reduction in orthogonal array can avoid exponential creation of solutions of OMOEA and improve the performance in robusticity without degrading precision and distribution of solutions. Experimental results show that OMOEA-II can solve problems with high dimensions and large number of local Pareto-optimal fronts better than some existing algorithms recently reported in the literatures.