DocumentCode :
2606218
Title :
Genetical swarm optimization: a new hybrid evolutionary algorithm for electromagnetics
Author :
Grimaldi, E.A. ; Grimaccia, F. ; Mussetta, M. ; Zich, R.E.
Author_Institution :
Politecnico di Milano, Dipartimento di Elettrotecnica, Piazza Leonardo da Vinci 32,20133, Milano, Italy
fYear :
2004
fDate :
14-17 Sept. 2004
Firstpage :
458
Lastpage :
460
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 different techniques are presented for an electromagnetic optimization problem.
Keywords :
Constraint optimization; Cultural differences; Electromagnetic modeling; Evolutionary computation; Genetic algorithms; Genetic mutations; Particle swarm optimization; Performance evaluation; Search methods; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mathematical Methods in Electromagnetic Theory, 2004. 10th International Conference on
Conference_Location :
Dniepropetrovsk, Ukraine
Print_ISBN :
0-7803-8441-5
Type :
conf
DOI :
10.1109/MMET.2004.1397080
Filename :
1397080
Link To Document :
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