Name
Abstract | ||
|---|---|---|
Constraint Directed Network Artificial Immune System is an artificial immune algorithm, recently proposed, to solve constraint satisfaction problems. The algorithm has shown to be able to solve hard instances. However, some problems are still unsolved using this approach. In this paper, we propose a method to improve the search done by the algorithm. Our method can be included in other immune algorithms which manage constraints. The tests are carried out to solve very hard instances randomly generated of 3-colouring problems. The results show that using our method, the algorithm is able to solve more problems in less execution time. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-03246-2_24 | ICARIS |
Keywords | Field | DocType |
3-colouring problem,constraint directed network artificial,execution time,hard instance,constraint satisfaction problem,immune algorithm,artificial immune algorithm,3-colouring problems,immune system,artificial immune system | Constraint satisfaction,Artificial immune system,Mathematical optimization,Computer science,Constraint graph,AC-3 algorithm,Constraint satisfaction problem,Execution time,Artificial intelligence,Artificial immune algorithm,Machine learning,Hybrid algorithm (constraint satisfaction) | Conference |
Volume | ISSN | Citations |
5666 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 17 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| María Cristina Riff | 1 | 200 | 23.91 |
| Elizabeth Montero | 2 | 69 | 10.14 |