Online Algorithm for Clustering with Capacity Constraints

Shivam Gupta, Shweta Jain, Narayanan C. Krishnan, Ganesh Ghalme, Nandyala Hemachandra

Abstract: Traditional clustering often results in imbalanced clusters, limiting its suitability for real-world problems. In response, capacitated clustering methods have emerged, aiming to achieve balanced clusters by limiting points in each cluster. In this paper, we introduce online algorithms with provable bounds on opened centers and cost approximation. We validate our methods experimentally.