基于改进遗传算法的电极优化方法的研究

Research of electrode optimizing method based on improving genetic algorithm

针对经典遗传算法在实际优化计算中由于早熟导致种群中个体样本多样性下降,影响优化进程及最优解质量等弊端,提出改进的遗传算法。通过引入种群秩的定义,从而实现对种群多样性的定量评估。通过综合判断函数的引入,实现了对早熟的准确判断。通过优秀个体选择策略及对种群等参数进行合理的处理,实现了优化效率的整体提升。通过电极优化的实例验证,证明该算法的正确性、可行性。

Aiming at the decline caused by prematurity in the variety of individual samples within classifications of classic genetic algorithm in practical computational methods ,as well as the defects of influencing process optimization ＆ the quality of optimum solution,the improved genetic algorithm was put forward. Through introducing the concept of classification rank ,rational evaluation of variety towards classification has thus been realized. Through judging the introduction of functions synthetically,the precise judgment towards prematurity has been realized. Through ＂Excellent Individual Selection Strategy＂ and the logical solution to parameters as classification,the monolithic improvement of optimization efficiency has been realized. Through instantial testification of electrode optimization,the correctness ＆feasibility of the algorithm has been proved.