An efficient multi-objective evolutionary algorithm: OMOEA-II. (English) Zbl 1109.68642

Coello Coello, Carlos A. (ed.) et al., Evolutionary multi-criterion optimization. Third international conference, EMO 2005, Guanajuato, Mexico, March 9–11, 2005. Proceedings. Berlin: Springer (ISBN 3-540-24983-4/pbk). Lecture Notes in Computer Science 3410, 108-119 (2005).
Summary: 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.
For the entire collection see [Zbl 1069.68002].


68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
90C29 Multi-objective and goal programming
90C59 Approximation methods and heuristics in mathematical programming


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