The Portfolio Optimization problem is a multi multi-objective resource allocation problem where money to be allocated to the assets is the resource. The problem consists of the selection of assets from thousands of them available in the market, weigh them proper ly in the portfolio in order to minimize the risk and maximize the expected return of the investment. In our work, the main motive is to make the portfolio more realistic, apart from achieving better results. We introduce mainly: 1) The inclusion of real l ife constraints namely ? realistic transaction costs, 2) The new co co-ordinate ascent Genetic Algorithm, taking into consideration the traded volumes . We compare our results with simple GA based method and the index, and observe a noticeable improvement.