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光学薄膜自动设计的多目标优化方法
. f) U- \& s- l* ^# I% c% n- y王文梁1 ,2 熊胜明1/ I, E B( D* s2 b: b6 b. j
(1 中国科学院光电技术研究所, 四川成都610209 ; 2 中国科学院研究生院, 北京100039)
" k3 T' z4 ~5 S& }- O- Z摘要 光学薄膜中已使用的优化方法都是单目标寻优的,通过分析光学薄膜优化设计的原理,将薄膜设计的物理8 y7 \) J) {2 g
问题归结为混合离散变量的多目标优化设计的数学模型,并认为这是薄膜设计的一般性模型,现行的单目标优化
6 T# u; u4 z. f7 z& }算法只是这个模型的简化。基于这一新思路,并结合多目标优化算法的研究现状,采用了一种基于免疫应答原理7 b2 P+ ^+ J* l7 J
的智能型多目标优化算法。该算法隐含并行处理能力,原理上是具备全局搜索能力的自适应随机性算法。将此算$ q1 @3 B6 E/ ]9 G- T
法运用到光学薄膜设计中,给出了一些优化的设计实例。结果表明,将多目标优化算法引入薄膜设计的新思路是
7 F' } Q, p2 J5 n& o1 q可行的,将来会有较好的发展前景。
$ P, H! D, G* ?) b5 M关键词 光学设计; 光学薄膜; 多目标优化; 免疫应答& R# B6 S) m8 u7 `
中图分类号 O484 文献标识码 A doi : 10. 3788/ AOS20082810. 2026
# ?4 K0 n8 r3 G7 \+ T; K BMul t i object i ve Op t imi z a t i o n App r oa c h of Op t ic a l Thi n Fi lm Des i g n& b* x7 s* i' P1 ~, c
Wang Wenliang 1 ,2 Xiong Shengming18 T! |3 i7 M* |: K+ k
1 Ins t i t ute of Op t ics a n d Elect ronics , Chi nese Academy of Sciences , Chengd u , Sich u a n 610209 , Chi n a
! X( {1 g; t& O0 d- \( d- s2 Gr a d ua te Unive rsi t y of Chi nese Aca demy of Sciences , Beiji ng 100039 , Chi n a6 e! m/ o# w' Z& y2 G" A0 L
Abs t r act All optimization methods used in optical thin film design can seek only one object . Af ter t he analysis of the2 ^# b# z7 o- v$ S$ d! |; x3 O! R
theory of optical thin film optimization design , it is p roposed that multiobjective optimization with mixed discrete1 v. H4 C# X9 V( x4 H, V. g& Y+ H5 ^
variable is the essential mathematical model and can reflect the p hysical essence of optical thin film design. The+ S, `8 M/ b5 f7 z: G+ {
optimization algorithm for single objective p roblem which has been widely used in the fields of optical thin film design, _) F8 c2 a0 N4 C& {1 w4 d9 V
is only a simplification. Based on this new consideration and the s tatus of multiobjective optimization research , an
4 v" v3 n+ O" ^) P/ E, ?immune response2based multiobjective optimization algorithm is adopted to design optical thin film. This algorithm
$ r @; y+ d1 U0 Q" X# W3 mcan implement parallel t reatment , and is a self2adaptive random algorithm with ove rall search capability in p rinciple .
; r) U9 x4 r. mThe algorithm is used in optical thin film design , and some examples are p resented. According to the results of
# b1 x; |; ]8 W5 cexpe riments , the idea of applying multiobjective optimization app roach to designing optical thin film can be realized in
A1 C* Z! v9 i+ ~theory and have a bright future .( I3 X* D2 f' _' V" v0 k. E
Key wor ds optical design ; optical t hin film; multiobjective optimization ; response of the immune system |
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