Name
Abstract | ||
|---|---|---|
Standard tabu search methods are based on the complete exploration of current solution neighborhood. However, for some problems with very large neighborhood or time-consuming evaluation, the total exploration of the neighborhood is impractical. In this paper, we present an adaptive exploration of neighborhood using extension and restriction mechanisms represented by a loop detection mechanism and a tabu list structure. This approach is applied to the K-coloring problem and evaluated on standard benchmarks like DIMACS in comparison with more powerful recently published algorithms. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICTAI.2006.68 | ICTAI |
Keywords | Field | DocType |
search problems,K-coloring problem,intelligent neighborhood exploration,local search heuristic,loop detection mechanism,tabu list structure,tabu search method | Hill climbing,Guided Local Search,Computer science,Beam search,Heuristics,Artificial intelligence,Local search (optimization),Tabu search,Machine learning | Conference |
ISSN | ISBN | Citations |
1082-3409 | 0-7695-2728-0 | 5 |
PageRank | References | Authors |
0.45 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isabelle Devarenne | 1 | 8 | 1.53 |
| Hakim Mabed | 2 | 100 | 14.07 |
| Alexandre Caminada | 3 | 107 | 23.61 |