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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...

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Detalles Bibliográficos
Autores principales: Lingwood, C, Burt, G, Gunn, K, Smith, J D A
Formato: info:eu-repo/semantics/article
Lenguaje:eng
Publicado: 2010
Materias:
Acceso en línea:http://cds.cern.ch/record/1306813
Descripción
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.