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TY - CONF AU - Huang, X. ED - Schaa, Volker RW ED - Power, Maria ED - Shiltsev, Vladimir ED - White, Marion TI - Development and Application of Online Optimization Algorithms J2 - Proc. of NAPAC2016, Chicago, IL, USA, October 9-14, 2016 C1 - Chicago, IL, USA T2 - North American Particle Accelerator Conference T3 - 3 LA - english AB - Automated tuning is an online optimization process. It can be faster and more efficient than manual tuning and can lead to better performance. Automated tuning is an online optimization process. It is more efficient than manual tuning and can lead to better performance. It may also substitute or improve upon model based methods. Noise tolerance is a fundamental challenge to online optimization algorithms. We discuss our experience in developing a high efficiency, noise-tolerant optimization algorithm, the RCDS method, and the successful application of the algorithm to various real-life accelerator problems. Experience with a few other online optimization algorithms are also discussed. A performance stabilizer and an interactive optimization GUI are presented. PB - JACoW CP - Geneva, Switzerland SP - 1287 EP - 1291 KW - ion KW - injection KW - GUI KW - coupling KW - operation DA - 2017/01 PY - 2017 SN - 978-3-95450-180-9 DO - 10.18429/JACoW-NAPAC2016-FRA2IO01 UR - https://jacow.org/napac2016/papers/fra2io01.pdf ER -