GRASP with path-relinking for data clustering: a case study for biological data

Cluster analysis has been applied to several domains with numerous applications. In this paper, we propose several GRASP with path-relinking heuristics for data clustering problems using as case study biological datasets. We hybridized the GRASP proposed by Nascimento et. al (2010) with four alternatives for relinking method: forward, backward, mixed, and randomized. To our knowledge, GRASP with path-relinking has never been applied to cluster biological datasets. Extensive comparative experiments with other algorithms on a large set of test instances, according to different distance metrics (Euclidean, city block, cosine, and Pearson), show that the best of the proposed variants is both effective and efficient.