Genetic Algorithms in Noisy Environments
Machine Learning
Averaging Efficiently in the Presence of Noise
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
An Automatic Multi-objective Adjustment System for Optical Axes using Genetic Algorithms
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
Multi-objective binary search optimisation
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
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The adjustment of optical axes is crucial for laser systems. We have previously proposed an automatic adjustment method using genetic algorithms to adjust the optical axes. However, there were still two problems that needed to be solved: (1)long adjustment times, and (2)adjustment precision due to observation noise. In order to solve these tasks, we propose a robust and efficient automatic multi-objective adjustment method using stochastic binary search algorithm. Adjustment experiments for optical axes with 4-DOF in noisy environment demonstrate that the proposed method can robustly adjust the positioning and the angle of the optical axes in about 12 minutes.