Name
Abstract | ||
|---|---|---|
In this article a new method to obtain the control parameters values for the Threshold Accepting algorithm is presented, which is independent of the problem domain and size. This approach differs from the traditional methods that require knowing first the problem domain, and then knowing how to select the parameters values to solve specific problem instances. The proposed method is based on a sample of problem instances, whose solution allows us to characterize the problem and to define the parameters. To test the method the combinatorial optimization model called DFAR was solved using the Threshold Accepting algorithm. The experimental results show that it is feasible to automatically obtain the parameters for a heuristic algorithm, which will produce satisfactory results, even though the kind of problem to solve is not known. We consider that the proposed method principles can be applied to the definition of control parameters for other heuristic algorithms. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-46016-0_13 | MICAI |
Keywords | Field | DocType |
control parameters value,threshold accepting algorithm,automatic generation,specific problem instance,problem instance,control parameters,new method,parameters value,heuristic algorithm,proposed method principle,problem domain,combinatorial optimization | Simulated annealing,Heuristic,Mathematical optimization,Problem domain,Computer science,Heuristic (computer science),Algorithm,Combinatorial optimization,Program specification | Conference |
ISBN | Citations | PageRank |
3-540-43475-5 | 8 | 0.68 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joaquín Pérez | 1 | 45 | 9.56 |
| Rodolfo Pazos | 2 | 19 | 2.16 |
| Laura Velez | 3 | 8 | 1.02 |
| Guillermo Rodriguez | 4 | 8 | 1.36 |