Multi‐objective genetic algorithm for synchrotron radiation beamline optimization

In beamline design, there are many floating parameters that need to be tuned; manual optimization is time‐consuming and laborious work, and it is also difficult to obtain well optimized results. Moreover, there are always several objectives that need to be considered and optimized at the same time,...

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Vydané v:Journal of synchrotron radiation Ročník 30; číslo 1; s. 51 - 56
Hlavní autori: Zhang, Junyu, Qi, Pengyuan, Wang, Jike
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.01.2023
John Wiley & Sons, Inc
Predmet:
Algorithms
beamline design
Computer Simulation
Design optimization
Dosage
genetic algorithm
Genetic algorithms
multi-objective optimization
Optimization
Radiation
Research Papers
Synchrotron radiation
Synchrotrons
genetic algorithm
beamline design
multi-objective optimization
ISSN:1600-5775, 0909-0495, 1600-5775
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Popis
Shrnutí:In beamline design, there are many floating parameters that need to be tuned; manual optimization is time‐consuming and laborious work, and it is also difficult to obtain well optimized results. Moreover, there are always several objectives that need to be considered and optimized at the same time, making the problem more complicated. For example, asking for both the flux and energy to be as large as possible is a usual requirement, but the changing trends of these two variables are often contradictory. In this study, a novel optimization method based on a multi‐objective genetic algorithm is introduced, the first attempt to optimize a beamline with multiple objectives. In order to verify this method, beamline ID17 of the European Synchrotron Radiation Facility (ESRF) is taken as an example for simulation, with energy and dose rate as objectives. The result shows that this method can be effective for beamline optimization, and an optimal solution set can be obtained within 30 generations. For the solutions whose objectives are both improved compared with those of ESRF beamline ID17, the maximums of energy and dose rate increase by around 7% and 20%, respectively. A universal optimization simulation method based on a multi‐objective genetic algorithm is introduced; this is the first attempt to optimize the elements of a beamline using this method.
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ISSN:1600-5775
0909-0495
1600-5775
DOI:10.1107/S1600577522010050