遗传算法在非线性地下水经济管理模型中的应用

APPLICATION OF GENETIC ALGORITHM TO NONLINER GROUNDWATER ECONOMIC MANAGEMENT MODEL

通常采用基于梯度的数学规划方法求解地下水管理模型，如线性规划和非线性规划。但对于高度非线性、非凸的优化问题，尤其是涉及到经济或环境的地下水管理模型，传统方法难以有效地寻找全局最优解。本文介绍了一种求解非线性地下水资源管理模型的遗传算法，并以山东羊庄盆地分布参数地下水系统非线性管理模型为例，给出了用遗传算法在求解这类问题的一般步骤。结果表明该方法能快速有效地找到全局最优解。

Classic techniques such as nonlinear programming are regularly used to solve groundwater optimization problems. However, these problems can be highly nonlinear and nonconvex mathematical programming problems, especially in the case of economic management model. As such, there is no guarantee that a global optimum will be found by these gradientbased methods. Genetic algorithm(GA), a new approach to nonlinear groundwater management problem, is presented in this paper. We introduced the methodology, model development, and results of applying the genetic algorithm approach to solve a nonlinear groundwater distributed parameter management model of Yangzhuang basin in Shangdong Province. The results show that genetic algorithm can effectively and efficiently be used to obtain globally (or, at least near globally) optimal solutions to these problems.