Title :
The hierarchical fair competition (HFC) model for parallel evolutionary algorithms
Author :
Hu, Jian Jun ; Goodman, Erik D.
Author_Institution :
Dept. of Comput. Sci. & Eng., Michigan State Univ., East Lansing, MI, USA
Abstract :
The HFC model for evolutionary computation is inspired by the stratified competition often seen in society and biology. Subpopulations are stratified by fitness. Individuals move from low-fitness subpopulations to higher-fitness subpopulations if and only if they exceed the fitness-based admission threshold of the receiving subpopulation, but not of a higher one. HFC´s balanced exploration and exploitation, while avoiding premature convergence, is shown on a genetic programming example
Keywords :
biology; convergence; evolutionary computation; parallel algorithms; HFC model; biology; evolutionary computation; fitness-based admission threshold; genetic programming; hierarchical fair competition model; higher-fitness subpopulations; low-fitness subpopulations; parallel evolutionary algorithms; premature convergence; society; stratified competition; Biological system modeling; Computational biology; Computational modeling; Computer science; Convergence; Evolution (biology); Evolutionary computation; Genetic mutations; Genetic programming; Hybrid fiber coaxial cables;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1006208