Name
Title | ||
|---|---|---|
Using self-adaptable probes for dynamic parameter control of parallel evolutionary algorithms |
Abstract | ||
|---|---|---|
Controlling parameters during execution of parallel evolutionary algorithms is an open research area. Some recent research have already shown good results applying self-calibrating strategies. The motivation of this work is to improve the search of parallel genetic algorithms using monitoring techniques. Monitoring results guides the algorithm to take some actions based on both the search state and the values of its parameters. In this paper, we propose a parameter control architecture for parallel evolutionary algorithms, based on self-adaptable monitoring techniques. Our approach provides an efficient and low cost monitoring technique to design parameters control strategies. Moreover, it is completely independant of the implementation of the evolutionary algorithm. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11425274_9 | ISMIS |
Keywords | Field | DocType |
self-adaptable monitoring technique,open research area,monitoring results guide,low cost monitoring technique,parameter control architecture,parallel evolutionary algorithm,parallel genetic algorithm,evolutionary algorithm,monitoring technique,parameters control strategy,self-adaptable probe,dynamic parameter control | Open research,Search algorithm,Evolutionary algorithm,Parallel algorithm,Computer science,Evolutionary computation,Evolutionary programming,Parameter control,Genetic algorithm,Distributed computing | Conference |
Volume | ISSN | ISBN |
3488 | 0302-9743 | 3-540-25878-7 |
Citations | PageRank | References |
1 | 0.37 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xavier Bonnaire | 1 | 85 | 11.88 |
| María Cristina Riff | 2 | 200 | 23.91 |