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Title: Multi-objective dynamic aperture optimization for storage rings

We report an efficient dynamic aperture (DA) optimization approach using multiobjective genetic algorithm (MOGA), which is driven by nonlinear driving terms computation. It was found that having small low order driving terms is a necessary but insufficient condition of having a decent DA. Then direct DA tracking simulation is implemented among the last generation candidates to select the best solutions. The approach was demonstrated successfully in optimizing NSLS-II storage ring DA.
Authors:
 [1] ;  [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Report Number(s):
BNL-114339-2017-JA
Journal ID: ISSN 0217-751X; TRN: US1800473
Grant/Contract Number:
SC0012704
Type:
Accepted Manuscript
Journal Name:
International Journal of Modern Physics A
Additional Journal Information:
Journal Volume: 31; Journal Issue: 33; Journal ID: ISSN 0217-751X
Publisher:
World Scientific
Research Org:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
Language:
English
Subject:
43 PARTICLE ACCELERATORS; NSLS-II; dynamic aperture; multi-objective optimization; storage ring
OSTI Identifier:
1413914

Li, Yongjun, and Yang, Lingyun. Multi-objective dynamic aperture optimization for storage rings. United States: N. p., Web. doi:10.1142/S0217751X1644019X.
Li, Yongjun, & Yang, Lingyun. Multi-objective dynamic aperture optimization for storage rings. United States. doi:10.1142/S0217751X1644019X.
Li, Yongjun, and Yang, Lingyun. 2016. "Multi-objective dynamic aperture optimization for storage rings". United States. doi:10.1142/S0217751X1644019X. https://www.osti.gov/servlets/purl/1413914.
@article{osti_1413914,
title = {Multi-objective dynamic aperture optimization for storage rings},
author = {Li, Yongjun and Yang, Lingyun},
abstractNote = {We report an efficient dynamic aperture (DA) optimization approach using multiobjective genetic algorithm (MOGA), which is driven by nonlinear driving terms computation. It was found that having small low order driving terms is a necessary but insufficient condition of having a decent DA. Then direct DA tracking simulation is implemented among the last generation candidates to select the best solutions. The approach was demonstrated successfully in optimizing NSLS-II storage ring DA.},
doi = {10.1142/S0217751X1644019X},
journal = {International Journal of Modern Physics A},
number = 33,
volume = 31,
place = {United States},
year = {2016},
month = {11}
}