Title :
Fully Informed Differential Evolution
Author :
Omran, Mahamed G H ; Engelbrecht, Andries P. ; Salman, Ayed ; Hamdan, Suha A.
Author_Institution :
Dept. of Comput. Sci., Gulf Univ. for Sci. & Technol.
Abstract :
Differential evolution (DE) is generally considered as a reliable, accurate, robust and fast optimization technique. DE has been successfully applied to solve a wide range of numerical optimization problems. A fully informed DE (FIDE) is proposed in this paper where each member of the individual´s neighborhood contributes to the new mutant vector. The performance of FIDE is investigated and compared with other versions of DE. The experiments conducted show that FIDE generally outperformed the other DE versions in all the benchmark functions
Keywords :
evolutionary computation; vectors; benchmark function; fully informed differential evolution; mutant vector; numerical optimization; Birds; Computer science; Genetic mutations; Neodymium; Particle swarm optimization; Probability distribution; Reliability engineering; Robustness; Stochastic processes; Topology;
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
DOI :
10.1109/ICCIAS.2006.294137
