English

Parameterized Algorithms for Editing to Uniform Cluster Graph

Data Structures and Algorithms 2025-02-06 v3 Computational Complexity

Abstract

We study the parameterized complexity of transforming graphs into Uniform Cluster graphs, where each component is an equal-sized clique. We consider Uniform Cluster Vertex Deletion (UCVD), Uniform Cluster Edge Deletion (UCED), Uniform Cluster Edge Addition (UCEA), Uniform Cluster Edge Editing (UCEE), Uniform Cluster Exclusive Vertex Splitting (UCEVS), and Uniform Cluster Inclusive Vertex Splitting (UCIVS). For UCVD, we provide a vertex kernel of size O(k3)\mathcal{O}(k^{3}) and an FPT algorithm with running time 2knO(1)2^{k} \cdot n^{\mathcal{O}(1)}, improving the known 3knO(1)3^{k} \cdot n^{\mathcal{O}(1)} algorithm. For edge-based variants, we obtain a O(k2)\mathcal{O}(k^{2}) vertex kernel for UCEE and linear vertex kernels for UCED and UCEA, improving the best-known results. Additionally, we present a 1.47knO(1)1.47^{k} \cdot n^{\mathcal{O}(1)} algorithm for UCED, improving upon the previous 2knO(1)2^{k} \cdot n^{\mathcal{O}(1)} bound. We develop a sub-exponential algorithm for UCED on everywhere dense graphs by reducing it to dd-Way Cut. Lastly, we study vertex splitting operations and provide vertex kernels of size 4k4k for both UCIVS and UCEVS.

Keywords

Cite

@article{arxiv.2404.10023,
  title  = {Parameterized Algorithms for Editing to Uniform Cluster Graph},
  author = {Ajinkya Gaikwad and Hitendra Kumar and Soumen Maity},
  journal= {arXiv preprint arXiv:2404.10023},
  year   = {2025}
}
R2 v1 2026-06-28T15:54:58.475Z