Name
Abstract | ||
|---|---|---|
In this paper, we propose a new method based on simulated annealing (SA) to solve the minimum dominating set problem. To deal
with the considered problem, a stochastic local search (SLS) method is built first to find local solutions next to given solutions.
Then, a simulated annealing algorithm is invoked to enhance the SLS method with the ability of escaping from local solutions.
Moreover, three trial solution generation mechanisms are used to improve iterate solutions. The experimental results have
shown the promising performance of the proposed SA-based method in comparison with some other meta-heuristics in terms of
solution qualities and computational costs. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s13042-011-0043-y | Int. J. Machine Learning & Cybernetics |
Keywords | Field | DocType |
minimum dominating setstochastic local searchsimulated annealingmeta-heuristics | Simulated annealing,Hill climbing,Mathematical optimization,Local optimum,Adaptive simulated annealing,Local search (optimization),Minimum dominating set,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
3 | 2 | 1868-808X |
Citations | PageRank | References |
9 | 0.50 | 26 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abdel-Rahman Hedar | 1 | 404 | 30.79 |
| Rashad Ismail | 2 | 20 | 1.13 |