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)


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.


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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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