Problem and Algorithm Fine-Tuning - A Case of Study using Bridge Club and Simulated Annealing

Sometimes, it is difficult to cope with a good set of values for the parameters of an algorithm that solves an specific optimization problem. This work presents a methodology for fine-tuning the parameters of a Simulated Annealing (SA) algorithm solving the Bridge Club (BC) problem. The methodology uses Covering Arrays as a tool that evaluates a set of values for the parameters of the SA so that it achieves its best performance when solving BC. The results in the experiments performed show that, using this methodology, the SA reached the optimal solution of the BC problem with a relatively small number of evaluations, in comparison with other strategies that solves BC.