遗传算法在光学薄膜优化设计中的应用

D.G. Li, A. Watson
{"title":"遗传算法在光学薄膜优化设计中的应用","authors":"D.G. Li, A. Watson","doi":"10.1109/ICCIMA.1999.798507","DOIUrl":null,"url":null,"abstract":"Optical thin films are used in a wide variety of optical components. An important aspect of modern thin film design work is the use of computers to match the multilayer parameters to a set of optical specifications such as a desired reflectance curve. There are several basic approaches to the design of thin film multilayer coatings. These include graphical, analytical and digital design methods. The latter, representing both local and global minimum seeking algorithms, are particularly powerful because they lend themselves to the design of coatings with much more complicated properties than is possible with the other methods. Many traditional optimization techniques, including simplex, gradient, and damped least squares method, have been used in this field. However, up to now it has not been possible to say if one of these techniques gives the optimal solution of the problem to be solved. A genetic algorithm is introduced to search for the optimal optical thin film design. The paper discusses the problem of thin film design in greater detail. It shows how a genetic algorithm can evolve the design for better performance. Examples of designs obtained by GA optimization techniques are given.","PeriodicalId":110736,"journal":{"name":"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Genetic algorithms in optical thin film optimisation design\",\"authors\":\"D.G. Li, A. Watson\",\"doi\":\"10.1109/ICCIMA.1999.798507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optical thin films are used in a wide variety of optical components. An important aspect of modern thin film design work is the use of computers to match the multilayer parameters to a set of optical specifications such as a desired reflectance curve. There are several basic approaches to the design of thin film multilayer coatings. These include graphical, analytical and digital design methods. The latter, representing both local and global minimum seeking algorithms, are particularly powerful because they lend themselves to the design of coatings with much more complicated properties than is possible with the other methods. Many traditional optimization techniques, including simplex, gradient, and damped least squares method, have been used in this field. However, up to now it has not been possible to say if one of these techniques gives the optimal solution of the problem to be solved. A genetic algorithm is introduced to search for the optimal optical thin film design. The paper discusses the problem of thin film design in greater detail. It shows how a genetic algorithm can evolve the design for better performance. Examples of designs obtained by GA optimization techniques are given.\",\"PeriodicalId\":110736,\"journal\":{\"name\":\"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIMA.1999.798507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Third International Conference on Computational Intelligence and Multimedia Applications. ICCIMA'99 (Cat. No.PR00300)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIMA.1999.798507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

光学薄膜广泛应用于各种光学元件中。现代薄膜设计工作的一个重要方面是利用计算机将多层参数与一组光学规格(如期望的反射率曲线)相匹配。薄膜多层涂层的设计有几种基本方法。这些方法包括图形、分析和数字设计方法。后者,代表了局部和全局最小搜索算法,特别强大,因为它们比其他方法更适合设计具有更复杂性质的涂层。传统的优化方法包括单纯形法、梯度法和阻尼最小二乘法。然而,到目前为止,还不可能说这些技术中的一种是否给出了待解决问题的最优解。引入遗传算法寻找光学薄膜的最优设计。本文较详细地讨论了薄膜的设计问题。它展示了遗传算法如何进化设计以获得更好的性能。给出了用遗传算法优化得到的设计实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithms in optical thin film optimisation design
Optical thin films are used in a wide variety of optical components. An important aspect of modern thin film design work is the use of computers to match the multilayer parameters to a set of optical specifications such as a desired reflectance curve. There are several basic approaches to the design of thin film multilayer coatings. These include graphical, analytical and digital design methods. The latter, representing both local and global minimum seeking algorithms, are particularly powerful because they lend themselves to the design of coatings with much more complicated properties than is possible with the other methods. Many traditional optimization techniques, including simplex, gradient, and damped least squares method, have been used in this field. However, up to now it has not been possible to say if one of these techniques gives the optimal solution of the problem to be solved. A genetic algorithm is introduced to search for the optimal optical thin film design. The paper discusses the problem of thin film design in greater detail. It shows how a genetic algorithm can evolve the design for better performance. Examples of designs obtained by GA optimization techniques are given.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信