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.
['Joaquín Pérez', 'Rodolfo Pazos', 'Laura Velez', 'Guillermo Gazzara Rodríguez']
Automatic Generation of Control Parameters for the Threshold Accepting Algorithm