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EVOLUTIONARY ALGORITHMS IN THE DESIGN OF CRAB CAVITIES
The design of RF cavities is a multivariate multiobjective problem. Manual optimisation is poorly suited to this class of investigation, and the use of numerical methods results in a non-differentiable problem. Thus the only reliable optimisation algorithms employ heuristic methods. Using an evoluti...
Autores principales: | , , , |
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Formato: | info:eu-repo/semantics/article |
Lenguaje: | eng |
Publicado: |
2010
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/1306813 |
Sumario: | The design of RF cavities is a multivariate multiobjective problem. Manual optimisation is poorly suited to this class of investigation, and the use of numerical methods results in a non-differentiable problem. Thus the only reliable optimisation algorithms employ heuristic methods. Using an evolutionary algorithm guided by Pareto ranking methods, a crab cavity design can be optimised for transverse voltage (V) while maintaining acceptable surface fields and the correct operating frequency. Evolutionary algorithms are an example of a parallel meta-heuristic search technique inspired by natural evolution. They allow complex, epistatic (non-linear) and multimodal (multiple optima and/or sub-optima) optimization problems to be efficiently explored. Using the concept of domination the solutions can be ordered into Pareto fronts. The first of which contains a set of cavity designs for which no one objective (e.g. the transverse voltage) can be improved without decrementing other objectives. |
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