Equipo Elitista de Algoritmos Evolutivos Multiobjetivo

With the extended use of Evolutionary Algorithms for Multiobjective Optimization in real world problems, it becomes necessary to improve their performance taking advantage of each algorithm virtue. For this purpose, a wellknown alternative is the incorporation of parallelism. Therefore, parallel multiobjective evolutionary algorithms are becoming an area of growing interest for practical applications, mainly in industrial, financial and applied engineering problems. Since these algorithms differ in performance for different kind of problems, an Elitist Team Algorithm combining different Multiobjective Evolutionary Algorithms is proposed in a Parallel Computation context. Experimental results validate this new proposal showing several advantages (and a few disadvantages) when it is compared to parallel implementations of diverse well-known multiobjective evolutionary algorithms.

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