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Proceedings Paper

Global and multi-objective optimization for lens design by real-coded genetic algorithms
Author(s): Isao Ono; Shigenobu Kobayashi; Koji Yoshida
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Paper Abstract

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 plural 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 an 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. We show that effectiveness of the proposed method in multi-objective lens optimization by applying it to a three-element lens design problem.

Paper Details

Date Published: 21 September 1998
PDF: 12 pages
Proc. SPIE 3482, International Optical Design Conference 1998, (21 September 1998); doi: 10.1117/12.321995
Show Author Affiliations
Isao Ono, Univ. of Tokushima (Japan)
Shigenobu Kobayashi, Tokyo Institute of Technology (Japan)
Koji Yoshida, Nikon Corp. (Japan)


Published in SPIE Proceedings Vol. 3482:
International Optical Design Conference 1998
Leo R. Gardner; Kevin P. Thompson, Editor(s)

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