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. All these variants are based on the construction and local search procedures introduced by Nascimento et. al [22]. We hybridized the GRASP proposed by Nascimento et. al [22] 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.