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Evolutionary algorithms (EAs) have been widely applied to solve many numerical and combinatorial optimization problems. A special paradigm of EAs has been promoted allowing several populations to co-evolve together. During evolution process these populations can be either cooperative or competitive. The cooperative co-evolution evolutionary algorithm (CCEA) has shown a great deal in solving large and complex problems. However, there are limited studies on parallelizing cooperative co-evolution evolutionary algorithms. In this paper, we propose an approach combining CCEA with a synchronous parallel model. The design especially facilitates solving large scale problems. We conducted a preliminary investigation with several experiments on benchmark large scale problems. The experimental results indicated a promising performance of the proposed algorithm on the selected problems.