计算机应用研究2018，Vol.35Issue(4)：1042-1045,4.DOI:10.3969/j.issn.1001-3695.2018.04.018
改进的自适应遗传算法在函数优化中的应用
Application of improved adaptive genetic algorithm in function optimization
摘要
Abstract
Adaptive genetic algorithm has been proposed to improve the performance of function optimization.However,there are some disadvantages for traditional adaptive genetic algorithm,such as low efficiency and instability.This study improved the adaptive genetic algorithm by adaptively altering the process of genetic algorithm,dynamically changed the Pc and Pm values,and used an elitist strategy.It used two complex function optimization problems for simulation.The result shows that the improved adaptive genetic algorithm has a great improvement in many aspects of the global optimization,such as the convergence rate,the optimal solution,and the stability.关键词
自适应遗传算法/函数优化/求解精度/种群适应度Key words
adaptive genetic algorithm/function optimization/solution precision/fitness values of the populations分类
信息技术与安全科学引用本文复制引用
杨从锐,钱谦,王锋,孙铭会..改进的自适应遗传算法在函数优化中的应用[J].计算机应用研究,2018,35(4):1042-1045,4.基金项目
国家自然科学基金资助项目(31300938,61462053,61300145) （31300938,61462053,61300145）
吉林大学符号计算与知识工程教育部重点实验室开放课题(93K172016K10) （93K172016K10）
