<![CDATA[In conducting stock investment, it is necessary to verify or spread the investment in order to form a stock portfolio with the proportion or optimal weight of every stock, good profit, and risk that can be borne by investors. Therefore, a system that can determine the optimal stock portfolio must be made by implementing distributed genetic algorithm. Distributed genetic algorithm generate chromosomes randomly at the certain interval as the representation of the stocks proportion. Then reproduction, evaluation and selection can be done based on the largest fitness derived from the calculation with single index model to find the return and risk. Distributed genetic algorithm has migration mechanism that able to maintain a diversity of individual variation. It is necessary to find out a broader solution which can produce a diverse and optimal stock portfolio. From the test result, distributed genetic algorithms can be applied properly and produce an optimal stock portfolio. The best parameter of the popsize test result is 80, the number of generations 150, 0.8 crossover rate (cr), and 0.2 mutation rate (mr) and the number of sub-optimal population of 10 to produce an optimal stock portfolio.]]>
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