自适应遗传算法在电器产品优化设计中的研究

Research on adaptive genetic algorithm in the optimization design of electrical products

传统的基于人工神经网络的电器产品优化方法,在对电器产品优化设计后花费的材料成本仍然较高,因此设计一种基于自适应遗传算法的电器产品优化方法。首先,依据电器产品设计基本性能需求,建立电器产品优化目标函数,包括电器产品材料成本和最小变电损耗;然后,引入一个新的函数作为种群是否早熟的判断依据,以降低计算时间,在此基础上对电器产品优化点编码;最后,利用自适应遗传算法实现电器产品优化设计。通过实验对比结果可知,此次设计的基于自适应遗传算法的电器产品优化方法比传统方法的电器产品设计成本低,证明了此次设计方法的有效性。

The traditional electrical product optimization method based on artificial neural network still costs a lot of materials after the optimization design of electrical products,so an electrical product optimization method based on adaptive genetic algorithm is designed.According to the basic performance requirements of electrical product design,the electrical product optimization objective function which includes the cost of electrical product materials and the minimum transformation loss is established.Then,a new function is introduced as the judging basis of whether the population is premature or not,so as to reduce the calculation duration.On this basis,the optimization point of electrical product is coded.Finally,the optimization design of electrical product is realized with the adaptive genetic algorithm.The results of contrastive experiments show that the design cost of electrical products optimization method based on adaptive genetic algorithm is lower than that of the traditional method,which proves the effectiveness of the designed method.