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中文摘要：
针对传统的遗传算法在云环境中迭代次数多、耗时长的缺陷,提出了一种改进的遗传算法,主要从执行时间及执行任务所需的费用两个方面来优化任务调度.通过建立任务调度模型,设计出相应的适应度函数、界限函数.仿真结果表明,在任务调度中运用改进的遗传算法,所需的平均等待时间要短,调度所需的费用也比传统的遗传算法要低.
英文摘要：
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.
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