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TY - CONF AU - Appel, S. AU - Chetvertkova, V. AU - Geithner, W. AU - Herfurth, F. AU - Krause, U. AU - Reimann, S. AU - Sapinski, M. AU - Schütt, P. AU - Ãsterle, D. ED - Schaa, Volker RW ED - Arduini, Gianluigi ED - Pranke, Juliana ED - Seidel, Mike ED - Lindroos, Mats TI - Automatized Optimization of Beam Lines Using Evolutionary Algorithms J2 - Proc. of IPAC2017, Copenhagen, Denmark, 14â19 May, 2017 C1 - Copenhagen, Denmark T2 - International Particle Accelerator Conference T3 - 8 LA - english AB - Due to the massive parallel operation modes at GSI accelerators, a lot of accelerator setup and re-adjustment has to be made by operators during a beam time. This is typically done manually using potentiometers and is very time-consuming. With the FAIR project the complexity of the accelerator facility increases further and for efficiency reasons it is recommended to establish a high level of automation for future operation. Modern Accelerator Control Systems allow a fast access to both, accelerator settings and beam diagnostics data. This provides the opportunity to implement algorithms for automated adjustment of e.g. magnet settings to maximize transmission and optimize required beam parameters. The fast-switching magnets in GSI-beamlines are an optimal basis for an automatic exploration of the parameter-space. The optimization of the parameters for the SIS18 multi-turn-injection using a genetic algorithm has already been simulated*. The first results of our automatized online parameter optimization at the CRYRING@ESR injector are presented here. PB - JACoW CP - Geneva, Switzerland SP - 3941 EP - 3944 KW - ion KW - injection KW - simulation KW - operation KW - quadrupole DA - 2017/05 PY - 2017 SN - 978-3-95450-182-3 DO - 10.18429/JACoW-IPAC2017-THPAB096 UR - http://jacow.org/ipac2017/papers/thpab096.pdf ER -