Optical Design with Epsilon-Dominated Multi-objective Evolutionary Algorithm

  • Shaine Joseph
  • Hyung W. Kang
  • Uday K. Chakraborty
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4431)

Abstract

Significant improvement over a patented lens design is achieved using multi-objective evolutionary optimization. A comparison of the results obtained from NSGA2 and ε-MOEA is done. In our current study, ε-MOEA converged to essentially the same Pareto-optimal solutions as the one with NSGA2, but ε-MOEA proved to be better in providing reasonably good solutions, comparable to the patented design, with lower number of lens evaluations. ε-MOEA is shown to be computationally more efficient and practical than NSGA2 to obtain the required initial insight into the objective function trade-offs while optimizing large and complex optical systems.

Keywords

Design Variable Optical Design Single Objective Optimization Code Versus Lens Evaluation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Shaine Joseph
    • 1
  • Hyung W. Kang
    • 1
  • Uday K. Chakraborty
    • 1
  1. 1.Department of Mathematics and Computer Science, University of Missouri, St. Louis, One University Blvd., St. Louis, MO 63121USA

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