改进的遗传算法在城市污水处理厂区间数优化设计模型中的应用

对于高度非线性的城市污水处理厂区间数优化设计模型(IPODM),若采用传统的方法求解,不仅计算繁琐,且难以有效地寻找全局最优解.本文通过引入遗传算法(GA),与传统的步长搜索法相结合,大大提高了问题的求解效率.本文给出了这种改进算法在某一城市污水处理厂优化设计中的应用实例.结果表明,不仅解的搜索效率有明显的提高,而且目标函数值在原有的基础上改进了20%,有着显著的经济效益;但是由于遗传算法自身的局限性,所求得的解只是一定条件下的最优区间解.

New way to apply improved genetic algorithm to optimal design model for municipal sewage-treating plants

This paper introduced a new way on how to apply the genetic algorithm to the improvement of the researching efficiency. As we know, classic optimization techniques are not only troublesome in calculation, but also low efficient for the highly non-linear interval parameter optimal design model (IPODM). The present paper has introduced the improved genetic algorithm into the optimized design for the municipal sewage treating plants with the IPODM, whose value has been clearly evidenced. Our research results show that not only the research efficiency has been improved significantly to save a lot of calculation time and other troubles, but also to increase the objective values by 20 percent which will bring about great economic cost-benefit. However, due to the limitations of the genetic algorithm itself, the calculation results are still not to be the most optimal global solutions, rather remaining to be a more optimal interval solution to some extent.