"In this paper a novel parallel meta-heuristic algorithm called MeTEO is presented, applied to the shape optimization of multistage depressed collectors, simulated by means of a Finite Element collector and electron gun simulator, COLLGUN, which uses the Constructive Solid Geometry for the description of the device shape. METEO is a hybrid algorithm composed by three different heuristics: FSO (Flock of Starlings Optimization), PSO (Particle Swarm Optimization), and BCA (Bacterial Chemotaxis Algorithm); it performs the optimization using both the topological and the metric rules and offers a natural parallel implementation that allows speeding up the whole process of optimization by the fitness modification (FM)."
Coco, S., Laudani, A., RIGANTI FULGINEI, F., Salvini, A. (2011). Shape Optimization of Multistage Depressed Collectors by Parallel Evolutionary Algorithm. IEEE TRANSACTIONS ON MAGNETICS, 48(2), 435-438 [10.1109/TMAG.2011.2174035].
Shape Optimization of Multistage Depressed Collectors by Parallel Evolutionary Algorithm
COCO, SALVATORE;LAUDANI, ANTONINO;RIGANTI FULGINEI, Francesco;SALVINI, Alessandro
2011-01-01
Abstract
"In this paper a novel parallel meta-heuristic algorithm called MeTEO is presented, applied to the shape optimization of multistage depressed collectors, simulated by means of a Finite Element collector and electron gun simulator, COLLGUN, which uses the Constructive Solid Geometry for the description of the device shape. METEO is a hybrid algorithm composed by three different heuristics: FSO (Flock of Starlings Optimization), PSO (Particle Swarm Optimization), and BCA (Bacterial Chemotaxis Algorithm); it performs the optimization using both the topological and the metric rules and offers a natural parallel implementation that allows speeding up the whole process of optimization by the fitness modification (FM)."I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
