Title :
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
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;
Conference_Titel :
Computational Electromagnetics and Its Applications, 2004. Proceedings. ICCEA 2004. 2004 3rd International Conference on
Print_ISBN :
0-7803-8562-4
DOI :
10.1109/ICCEA.2004.1459314
