Optimal lens design by real-coded genetic algorithms using UNDX

被引:38
作者
Ono, I
Kobayashi, S
Yoshida, K
机构
[1] Tokyo Inst Technol, Yokohama, Kanagawa 2268501, Japan
[2] Univ Tokushima, Tokushima 7708506, Japan
[3] Nikon Inc, Shinagawa 1408601, Japan
关键词
lens design; real-coded genetic algorithms; global optimization; multi-objective optimization; UNDX; MGG;
D O I
10.1016/S0045-7825(99)00398-9
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents new lens optimization methods based on real-coded genetic algorithms (GAs). We take advantage of GA's capability of global optimization and multi-objective optimization against two serious problems in conventional lens optimization techniques: (1) choosing a starting point by trial and error, and (2) combining multiple criteria to a single criterion. In this paper, two criteria for lenses, the resolution and the distortion, are considered. First, we propose a real-coded GA that optimizes a single criterion, a weighted sum of the resolution and the distortion. To overcome a problem of the difficulty in generating feasible lenses especially in large-scale problems, we introduce a feasibility enforcement operator to modify an infeasible solution into a feasible one. By applying the proposed method to some small-scale problems, we show that the proposed method can find empirically optimal and suboptimal lenses. We also apply the proposed method to some relatively large-scale problems and show that the proposed method can effectively work under large-scale problems. Next, regarding the lens design problem as a multi-objective optimization problem, we propose a real-coded multi-objective GA that explicitly optimizes the two criteria, the resolution and the distortion. We show the effectiveness of the proposed method in multi-objective lens optimization by applying it to a three-element lens design problem. (C) 2000 Published by Elsevier Science S.A. All rights reserved.
引用
收藏
页码:483 / 497
页数:15
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