A new hybrid genetical-swarm algorithm for electromagnetic optimization

Author

Grimaldi, E. Alfassio ; Grimaccia, F. ; Mussetta, M. ; Pirinoli, P. ; Zich, R.E.

Author_Institution

Dipt. di Elettrotecnica, Politecnico di Milano, Italy

fYear

2004

fDate

1-4 Nov. 2004

Firstpage

157

Lastpage

160

Abstract

A new hybrid evolutionary algorithm called GSO (genetical swarm optimization) Is here presented. GSO combines the well known particle swarm optimization and genetic algorithms. The 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. A detailed description of the algorithm and numerical comparison of the different techniques are presented for a typical electromagnetic optimization problem.

Keywords

computational electromagnetics; genetic algorithms; GSO; PSO; combinatorial optimization problems; cultural evolution; electromagnetic optimization; evolutionary algorithm; genetic algorithms; genetical swarm optimization; hybrid genetical-swarm algorithm; natural selection; particle swarm optimization; population- based heuristic search technique; social evolution; social interaction emulation; Context modeling; Convergence of numerical methods; Cultural differences; Evolution (biology); Evolutionary computation; Genetic algorithms; Particle swarm optimization; Performance evaluation; Stochastic processes; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on

Print_ISBN

0-7803-8562-4

Type

conf

DOI

10.1109/ICCEA.2004.1459314

Filename

1459314