Genetic algorithms have been applied to solve the
2-page drawing problem successfully, but they work
with one global population, so the search time and
space are limited. Parallelization provides an attractive
prospect in improving the efficiency and solution
quality of genetic algorithms. One of the most popular
tools for parallel computing is Message Passing
Interface (MPI). In this paper, we present four island
models of Parallel Genetic Algorithms with MPI: island
models with linear, grid, random graph topologies,
and island model with periodical synchronisation.
We compare their efficiency and quality of solutions for
the 2-page drawing problem on a variety of graphs.
History
School
Science
Department
Computer Science
Pages
308149 bytes
Citation
HE, SÝKORA and MÄKINEN, 2006. Various island-based parallel genetic algorithms for the 2-page drawing problem. IN: FAHRINGER, T. (ed.), Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Networks, Innsbruck, Austria, February 14-16. Zurich : Acta Press