Optical Design with Epsilon-Dominated Multi-objective Evolutionary Algorithm

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 tradeoffs while optimizing large and complex optical systems.

• Type: Conference
• Year: 2007
• Where: ICANNGA
• Authors: Shaine Joseph, Hyung W. Kang, Uday K. Chakraborty
• Keywords: Algorithms, ICANNGA 2007, Multi-objective Evolutionary Optimization, Objective Function Tradeoffs, Patented Lens Design