Abstract: An improved genetic algorithm was proposed to solve the problem of more iterative times and cost more time in traditional genetic algorithm. The algorithm was designed to optimize the task scheduling mainly from two aspects: the execution time and the cost of the mission. The corresponding fitness function and boundary function were designed by establishing the task scheduling model. The results showed that,  in task scheduling using genetic algorithm, the average waiting time was shorter and scheduling costs required lower than that of the traditional genetic algorithm