Name
Abstract | ||
|---|---|---|
The aim of this paper is to present an experimental evaluation of a parallel genetic algorithm using MPI. The performance of the algorithm is verified by computational experiments on a real world data set, ran in a cluster of workstations. MPI seems to be appropriate for these kind of experiments as the results are reliable and efficient. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/PCI.2009.38 | Panhellenic Conference on Informatics |
Keywords | Field | DocType |
experimental evaluation,real world data,parallel genetic algorithm,computational experiment,genetics,parallel algorithms,parallel algorithm,clustering algorithms,computer experiment,probability density function,parallel processing,genetic algorithms,data mining,mpi,message passing,genetic algorithm,message passing interface,distributed computing,machine learning | Parallel genetic algorithm,Parallel algorithm,Computer science,Parallel processing,Parallel computing,Workstation,Message Passing Interface,Cluster analysis,Message passing,Genetic algorithm | Conference |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elias Hadjikyriacou | 1 | 0 | 0.34 |
| Nikolaos Samaras | 2 | 105 | 15.65 |
| Konstantinos Margaritis | 3 | 9 | 3.26 |