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This study investigates the performance of the weight optimization by comparing the performance of the portfolios of fund of funds (FoF) constructed by the Markowitz Mean-Variance (MV) model or Genetic Algorithm (GA) to that of S&P 500 and that of equal weight portfolio of Mutual funds. The chosen target funds are denominated in U.S. dollar or euros, and are chosen from the European market, United European market, Emerging market, Pacific market, South Asia market, Asia Pacific Zone market, American market, and Global market. The study period started on February 1, 1998 and ended on December 1, 2006. In this thesis, we test whether the Genetic Algorithm can beat the traditional Markowitz Mean- Variance model or not. At last, we get some results from empirical evidence. First, the Genetic Algorithm model performs better than the Markowitz Mean-Variance in performance measures of Sharpe, Treynor and Jensen's alpha. Second, both the Markowitz Mean-Variance model and Genetic Algorithm can beat the equal weight portfolios. Finally, the Markowitz Mean-Variance model and the Genetic Algorithm are not better than market index significantly.