Optical Design with Epsilon-Dominated Multi-objective Evolutionary Algorithm
- Cite this paper as:
- Joseph S., Kang H.W., Chakraborty U.K. (2007) Optical Design with Epsilon-Dominated Multi-objective Evolutionary Algorithm. In: Beliczynski B., Dzielinski A., Iwanowski M., Ribeiro B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg
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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