用遗传算法优化工业污染源布局

工业污染源的优化布局是复杂的以偏微分方程为约束条件的控制问题。遗传算法是一种近年发展起来并广泛应用于多个领域优化问题的最优化方法。引入罚函数来处理环境不等式约束，建立了适当的编码方式和适应度函数，应用遗传算法以求解优化布局问题，并进行了数值试验。数值试验结果表明，遗传算法可以有效地用于求解工业污染源的优化布局问题，而且该方法鲁棒性好，适用于任意的目标函数和空气污染模式，天然适合于并行计算，有很好的应用前景。

Genetic Algorithm to Optimize Planning of Industrial Pollutant Sources

The optimal planning of industrial pollutant sources is a complicated non-linear optimum control problem object to partial differential equations. The genetic algorithm,a kind of new method for optimization has been used in many fields to solve optimization problems.In this paper,penalty function is introduced to deal with environmental inequality constrains,an appropriate method of coding as well as fitness function is chosen, and the genetic algorithm is applied to solve the optimal problem.The validation and efficiency of genetic algorithms is verified through numerical experiments.Furthermore,this kind of genetic algorithm is robust as well as naturally parallel,and it can adapt to various of object functions and air quality models.All these good features make genetic algorithm broad prospect in the field of environment.