改进的模拟退火遗传算法在地下水管理中的应用

Application of improved simulated annealing genetic algorithm to groundwater management

摘要: 对于高度非线性、非凸的地下水管理模型,传统优化方法难以找到全局最优解。本文采用模拟退火遗传算法求解地下水管理模型,并从三个方面对算法进行改进:引入小生境技术,采用自适应交叉和变异概率,在选择过程中采用最优保存策略,从而提高算法的全局寻优能力和收敛速度。采用惩罚函数法处理约束条件。用Fortran 90语言编制了计算程序,并通过Schaffer测试函数验证了该算法不仅具有强大的全局寻优能力和局部搜索能力,而且具有较快的收敛速度和较高的优化精度。将该算法应用到某研究区地下水管理中,取得了较好的效果。

Abstract: For a highly nonlinear and nonconvex groundwater management model,the traditional optimization methods are difficult to find the global optimum.Simulated annealing genetic algorithm was used to solve a groundwater management model in this paper and was improved from three aspects to enhance the ability of global optimization and convergence speed:(1) introducing the niche technology,(2) using adaptive crossover probability and mutation probability,and(3) using the elitist strategy during the sel...