Name
Title | ||
|---|---|---|
Self-calibrating strategies for evolutionary approaches that solve constrained combinatorial problems |
Abstract | ||
|---|---|---|
In this paper, we evaluate parameter control strategies for evolutionary approaches to solve constrained combinatorial problems. For testing, we have used two well known evolutionary algorithms that solve the Constraint Satisfaction Problems GSA and SAW. We contrast our results with REVAC, a recently proposed technique for parameter tuning. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-68123-6_29 | ISMIS |
Keywords | Field | DocType |
parameter control strategy,evolutionary algorithm,self-calibrating strategy,combinatorial problem,constraint satisfaction,evolutionary approach,parameter tuning,evolutionary algorithms,constraint satisfaction problem | Mathematical optimization,Evolutionary algorithm,Computer science,Constraint satisfaction problem,Artificial intelligence,Evolutionary programming,Parameter control,Calibration,Machine learning | Conference |
Volume | ISSN | ISBN |
4994 | 0302-9743 | 3-540-68122-1 |
Citations | PageRank | References |
4 | 0.40 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elizabeth Montero | 1 | 69 | 10.14 |
| María Cristina Riff | 2 | 200 | 23.91 |