To improve the migration performance and the execution efficiency of mobile agent systems, a route plan for mobile agents based on a combined intelligent algorithm composed of genetic algorithm and ant colony algorithm is provided in this paper. Genetic algorithm has the ability of doing a global searching quickly and stochastically, but it can not make use of enough system out-put information, and the efficiency to solve precision results is reduced. The ant colony algorithm is a novel simulated evolutionary algorithm which shows many good properties, but the speed at which the ant algorithm gives the solution is slow. New method combines the advantages of above two algorithms, and it increases the convergence speed of genetic algorithm and enhances the ability of working out the correct solution of ant colony algorithm. The mixed algorithm includes two steps: The first step is using genetic algorithm to get the initial pheromone distributing; and the second step is adopting the ant colony algorithm to generate the global optimal path for the mobile agent. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the only genetic algorithm from time efficiency or only ant colony algorithm from reaching result efficiency in the global optimal path planning.
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