Data Clustering Using Mother Tree Optimization

Wael Korani, Malek Mouhoub

2025

Abstract

Clustering is the process of dividing data objects into different groups called clusters, without prior knowledge. Traditional clustering techniques might suffer from stagnation, where the solution is stuck in a local optimum. In the last decade, many metaheuristics, including swarm intelligence, have been applied to address the problem of clustering stagnation in a reasonable time. We propose a new clustering framework that is based on metaheuristics and, more precisely, swarm intelligence optimization algorithms that include particle swarm optimization (PSO) (Kennedy and Eberhart, 1995), whale optimization algorithm (WOA) (Mirjalili and Lewis, 2016), bacterial foraging optimization algorithm (BFOA) (Das et al., 2009) and mother tree optimization (MTO). To evaluate the performance of our framework and the new metaheuristic based on MTO called CMTO, we conducted a set of experiments on eight different datasets and using four different metrics: rand coefficient, Jaccard coefficient, distance matrix and running time. The results show that MTOC outperforms BF and WOA in terms of random coefficient (accuracy) in five of the eight instances.

Paper Citation

in Harvard Style

Korani W. and Mouhoub M. (2025). Data Clustering Using Mother Tree Optimization. In Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES; ISBN 978-989-758-732-0, SciTePress, pages 215-220. DOI: 10.5220/0013105300003893

in Bibtex Style

@conference{icores25,
author={Wael Korani and Malek Mouhoub},
title={Data Clustering Using Mother Tree Optimization},
booktitle={Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES},
year={2025},
pages={215-220},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013105300003893},
isbn={978-989-758-732-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES
TI - Data Clustering Using Mother Tree Optimization
SN - 978-989-758-732-0
AU - Korani W.
AU - Mouhoub M.
PY - 2025
SP - 215
EP - 220
DO - 10.5220/0013105300003893
PB - SciTePress