Parallel genetic algorithms on line topology of heterogeneous computing resources

This paper evaluates a parallel genetic algorithm (GA) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is investigated on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangement of computing capability. Their differences in chromosome variety, migration frequency and solution quality are investigated. The results in this paper can help to design parallel GAs in grid computing environments. Categories and Subject Descriptors F.2 [Analysis of algorithms and problem complexity]: Miscellaneous General Terms Algorithms, Design Keywords parallel genetic algorithm, migration interval, heterogeneous computing capability, grid

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Yiyuan Gong, Morikazu Nakamura, Shiro Tamaki
• Keywords: GECCO 2005, Heterogeneous Computing, Heterogeneous Computing Resources, Parallel Genetic Algorithm