光学精密工程2017，Vol.25Issue(3)：706-711,6.DOI:10.3788/OPE.20172503.0706
浮点数编码改进遗传算法在平面度误差评定中的研究
The research of floating-point codingimproved genetic algorithmin flatnesserror evaluation
摘要
Abstract
With rapid development of intelligent manufacturing system,using Meta heuristic method to quickly and accurately calculate the flatness error is of great practical significance.To further improve the accuracy of flatness error calculation,an improved genetic algorithm based on floating-point coding was studied.In this method,the simulated annealing idea was introduced and a mathematic model for minimum zone method was established based on crossover and variation of the original genetic algorithm;and then the optimal fitness convergence curve and average fitness convergence curve were obtained through computer simulation.The optimization results show that compared with traditional genetic algorithm,the accuracy of flatness error calculation is improved by 33.67％.The algorithm adopts floating-point coding,three section cross,turning wheel selection and optimal preservation strategy;and its overall performance can be improved by local search advantage of the simulated annealing algorithm.Being more convenient for computer programming,the algorithm can be further applied to other high-accuracy position and dimension calculations of intelligent measuring instruments.关键词
遗传算法/退火算法/最小包容区域/平面度误差评定Key words
genetic algorithm/annealing algorithm/minimum zone/flatness error evaluation引用本文复制引用
杨健,赵宏宇..浮点数编码改进遗传算法在平面度误差评定中的研究[J].光学精密工程,2017,25(3):706-711,6.基金项目
机器人,国家高技术863-809专题专家组 （）
成都理工大学机械工程创新团队(No.10912-JXTD201501) （No.10912-JXTD201501）
