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https://doi.org/10.18429/JACoW-IPAC2017-THPAB008
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
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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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
Copyright © 2017 by JACoW, Geneva, Switzerland     CC-BY Creative Commons License
cc Creative Commons Attribution 3.0