Title |
Particle Swarm Optimization Algorithm Applied in Online Commissioning at the MLS and BESSY II |
Authors |
- J. Li, J. Feikes, P. Goslawski, M. Ries
HZB, Berlin, Germany
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Abstract |
Particle Swarm Optimization (PSO) is a population based optimization technique inspired by the social behaviour of bird flocking. This algorithm has been successfully used for beam dynamics simulation due to its excellent capability to deal with large-dimensional optimization problems. At the MLS and BESSY II PSO was first successfully applied to improve the lifetime by 20~30% within only 10 iterations respectively. Now the PSO has been implemented as a multifunctional online optimizer to improve the machine performance. This paper presents some results of online experiments.
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Paper |
download THPAB008.PDF [0.374 MB / 4 pages] |
Export |
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Conference |
IPAC2017, Copenhagen, Denmark |
Series |
International Particle Accelerator Conference (8th) |
Proceedings |
Link to full IPAC2017 Proccedings |
Session |
Posters Thursday 1 |
Date |
18-May-17 16:00–18:00 |
Main Classification |
05 Beam Dynamics and Electromagnetic Fields |
Sub Classification |
D11 Code Developments and Simulation Techniques |
Keywords |
sextupole, injection, storage-ring, simulation, dynamic-aperture |
Publisher |
JACoW, Geneva, Switzerland |
Editors |
Volker RW Schaa (GSI, Darmstadt, Germany); Gianluigi Arduini (CERN, Geneva, Switzerland); Juliana Pranke (ESS, Lund, Sweden); Mike Seidel (PSI, Villigen, Switzerland); Mats Lindroos (ESS, Lund, Sweden) |
ISBN |
978-3-95450-182-3 |
Published |
May 2017 |
Copyright |
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