Related Experiment Video
Updated: Jun 23, 2025

Quasi-light Storage for Optical Data Packets
Published on: February 6, 2014
Nonlinear optimization for a low-emittance storage ring
Bonghoon Oh1, Jinjoo Ko1, Seunghwan Shin1
1Department of Accelerator Science, Korea University, 2511 Sejong-ro, Sejong 30019, South Korea.
Abstract:
A multi-objective genetic algorithm (MOGA) is a powerful global optimization tool, but its results are considerably affected by the crossover parameter ηc. Finding an appropriate ηc demands too much computing time because MOGA needs be run several times in order to find a good ηc. In this paper, a self-adaptive crossover parameter is introduced in a strategy to adopt a new ηc for every generation while running MOGA. This new scheme has also been adopted for a multi-generation Gaussian process optimization (MGGPO) when producing trial solutions. Compared with the existing MGGPO and MOGA, the MGGPO and MOGA with the new strategy show better performance in nonlinear optimization for the design of low-emittance storage rings.
Related Concept Videos
Conservation of Linear Momentum for a System of Particles
The impulsive force at play during this interaction is of extremely short duration, rendering its impulse negligible. When...
Stress Concentrations in Circular Shafts
NMR Spectrometers: Resolution and Error Correction
Linear Approximation in Frequency Domain
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
Radiation Pressure: Problem Solving
The average value of the rate of momentum transfer divided by the absorbing area represents the average force...

