Archivio Istituzionale della RicercaThis paper presents a new hybrid evolutionary algorithm combining Particle Swarm Optimization and Genetic Algorithms, called GSO (Genetical Swarm Optimization). GSO algorithm is essentially a population-based heuristic search technique which can be used to solve combinatorial optimization problems, modeled on the concept of natural selection but also based on cultural and social evolution. Numerical results and comparison of the dillerent techniques are presented for an electromagnetic optimization problem.
Genetical swarm optimization: a new hybrid evolutionary algorithm for electromagnetics / E., ALFASSIO GRIMALDI; F., Grimaccia; Mussetta, Marco; R. E., Zich. - (2004), pp. 458-460. (Intervento presentato al convegno MMET'04 10th International Conference on Mathematical Methods in Electromagnetic Theory tenutosi a Dniepropetrovsk, Ukraine nel Sept. 14-17, 2004) [10.1109/MMET.2004.1397080].
Genetical swarm optimization: a new hybrid evolutionary algorithm for electromagnetics
MUSSETTA, MARCO;
2004
Abstract
This paper presents a new hybrid evolutionary algorithm combining Particle Swarm Optimization and Genetic Algorithms, called GSO (Genetical Swarm Optimization). GSO algorithm is essentially a population-based heuristic search technique which can be used to solve combinatorial optimization problems, modeled on the concept of natural selection but also based on cultural and social evolution. Numerical results and comparison of the dillerent techniques are presented for an electromagnetic optimization problem.
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https://hdl.handle.net/11583/1921447
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