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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.
Due to improper design of fitness function in genetic algorithm search guide, it will be difficult to reflect the effect of individual differences and selection operations, resulting in the problem of premature convergence. Two models of fitness function based on order are constructed. So that the selection pressure is controlled in the process of evolution, the population competitiveness is enhanced and the premature phenomenon is improved. The improved algorithm is applied to the problem of complex function optimization. The results of MATLAB optimization show that the algorithm has good performance in population diversity, search speed, Have improved, and promote the application of genetic algorithms in engineering.