摘要
针对遗传算法搜索导优中适应度函数的设计不当,将难以体现个体差异和选择操作的作用,从而造成早熟收敛的问题,构建了两种基于顺序的适应度函数的模型.适应度函数的设计使得在进化过程中控制选择压力,种群竞争力得到增强,早熟现象得到改善.并将改进的算法应用在复杂函数优化问题上,MATLAB优化结果表明,算法在种群多样性、搜索速度、计算精度上均有改善,推动遗传算法在工程领域的应用.
Aiming at the design of fitness function problem in genetic algorithm that will lead to difficultly reflect the role of individual differences and selection operation, result- ing in premature convergence problem, we have designed two kinds of fitness function of genetic algorithm based on the sequence. The design of fitness function can control selec- tion pressure in the process of evolutionary and enhance the population competitiveness, so precocious phenomenon is improved. And apply the improved algorithm on the com- plex function optimization problems, MATLAB optimization results show that the fitness function based on sequence improves the population diversity and search speed, calculation accuracy, promoting genetic algorithm applied in engineering field.
出处
《数学的实践与认识》
北大核心
2015年第16期232-238,共7页
Mathematics in Practice and Theory
基金
国家自然科学基金(31071331)
关键词
遗传算法
改进适应度函数
函数优化
genetic algorithm
improved the fitness function
function optimization
