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@InProceedings{piselli:icalepcs2019-wepha124,
author = {E. Piselli and A. Akroh and K. Blaum and M. Door and D. Leimbach and S. Rothe},
title = {{CERN Accelerators Beam Optimization Algorithm}},
booktitle = {Proc. ICALEPCS'19},
pages = {1379--1384},
paper = {WEPHA124},
language = {english},
keywords = {experiment, ISOL, controls, simulation, operation},
venue = {New York, NY, USA},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {17},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2020},
issn = {2226-0358},
isbn = {978-3-95450-209-7},
doi = {10.18429/JACoW-ICALEPCS2019-WEPHA124},
url = {https://jacow.org/icalepcs2019/papers/wepha124.pdf},
note = {https://doi.org/10.18429/JACoW-ICALEPCS2019-WEPHA124},
abstract = {In experimental physics, computer algorithms are used to make decisions to perform measurements and different types of operations. To create a useful algorithm, the optimization parameters should be based on real time data. However, parameter optimization is a time consuming task, due to the large search space. In order to cut down the runtime of optimization we propose an algorithm inspired by the numerical method Nelder-Mead. This paper presents details of our method and selected experimental results from high-energy (CERN accelerators) to low-energy (Penning-trap systems) experiments as to demonstrate its efficiency. We also show simulations performed on standard test functions for optimization.},
}