Cluster analysis using metaheuristic algorithms has earned increasing popularity over recent years due to the great success of these algorithms in finding high-quality clusters in complex real-world ...

Traditional scalable clustering algorithms mainly deal with the clustering of linearly separable data, but it is challenging to cluster the non-linear separable data efficiently in the feature space.

The algorithm allows researchers to reconstruct how abundant different block-lengths are present within a copolymer sample, giving a much more detailed picture of the material's internal structure.