实验结果表明：提出的算法比现有的遗传算法以及传统的启发式方法提供了较好的结果。
The experimental results show that the proposed algorithm has a better performance than those of a traditional heuristic algorithm and an existing evolutionary algorithm.
其次把传统的解析法、迭代法以及遗传算法相结合，给出集成模型的计算步骤；
Secondly combining the traditional analytic method, iterative method, and GA(genetic algorithm) effectively, the calculation steps for the integrated model were given.
该算法对传统遗传算法的编码方式、群体规模以及遗传算子等方面进行了改进，利用专家知识辅助搜寻可行解，并提出罚因子的自适应调整。
This algorithm improves the method of coding, size of population and operators; USES expert knowledge to aid searching feasible solution; and presents self adaptive adjusting of penalty factor.
该算法对传统遗传算法的编码方式、群体规模以及遗传算子等方面进行了改进，利用专家知识辅助搜寻可行解，并提出罚因子的自适应调整。
This algorithm improves the method of coding, size of population and operators; USES expert knowledge to aid searching feasible solution; and presents self adaptive adjusting of penalty factor.
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