摘要
针对遗传算法(GA)优化超多参量光学系统时鲁棒性较差的问题,在混入逃逸函数实数编码GA(MERCGA)的基础上,进一步结合参量归一化和自适应变异概率的措施,提出了自适应归一化实数编码GA(ANRCGA)。用ANRCGA对鱼眼镜头光学系统案例进行优化设计,并应用评价函数和Zemax光线追迹方法对MERCGA和ANRCGA的优化结果作比较。结果表明,应用本文的ANRCGA比引自专利的参考设计及MERCGA优化得到光学系统的成像质量有明显提高,算法的鲁棒性和计算效率也到了改善。
For the issue of poor robustness of genetic algorithm （GA） in optimization of optical systems with super-multiple parameters, an improved genetic algorithm is developed by incorporating normaliza- tion of parameters and self-adaptive mutation probability into the real-coded genetic algorithm mixed with escape function （MERCGA）. The discussed algorithm （ANRCGA） and MERCGA are applied to optimize a fisheye lens whose imaging performances resulting from the two algorithms are evaluated by ray-tracing calculation with Zemax and evaluation function for comparison. The study shows that the for- mer has better imaging performance than the latter as well as the reference design from the patent. The proposed algorithm has better robustness and calculation efficiency in optimization of optical systems.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2015年第4期655-661,共7页
Journal of Optoelectronics·Laser
基金
国家自然科学基金(11274223)
上海市教委创新基金(12ZZ088)资助项目
