基于改进的GP实现组合逻辑电路的设计研究

由于遗传程序设计是一种随机性很强的全局搜索优化算法,是否能够收敛到全局最优解与初始群体的质量、参数选取、遗传操作及适应值的测试方式等有很大关系。因此,有必要对遗传程序设计进行改进,从而提高其收敛性能。本文主要介绍了遗传程序设计的改进策略以及基于改进的GP实现组合电路的进化设计思想,并且进行了算法性能的改进实验,得到了令人满意的结果。

GP to achieve improvement Based on the logic of the combination of design

As the genetic programming is a very strong global stochastic search algorithm,the possibility of convergence to the global optimum with the initial group of quality parameters of selection,genetic operation and the fitness test,and so there is A great relationship.Therefore,it is necessary to improve the genetic programming carried out so as to enhance the performance of theirconvergence.Thispaper describes the genetic programming strategy to improve based on improved,as well as the GP circuit combination to achieve the evolution of design and carry out the algorithm to improve the performance of the experiment,the results have been satisfactory.