Tuning of Clustering Search Based Metaheuristic by Cross-Validated Racing Approach

摘要

The success of a metaheuristic is directly tied to the good configuration of its free parameters, this process is called Tuning. However, this task is, usually, a tedious and laborious work without scientific robustness for almost all researches. The absence of a formal definition of the tuning and diversity of metaheuristic research contributes to the difficulty in comparing and validating the results, making the progress slower. In this paper, a tuning method named Cross-Validated Racing (CVR) is proposed along with the so named Biased Random-Key Evolutionary Clustering Search and applied to solve instances of the Permutation Flow Shop Problem (PFSP). The proposed approach has reached 99.1% of accuracy in predicting the optimal solution with the parameters found by Irace tuning method. Configurations generated by Irace, even different, have obtained results with the same statistical relevance.