@Article{cmc.2026.075234,
AUTHOR = {Maryem Lachgar, Mansour Lmkaiti, Ibtissam Larhlimi, Imad Aattouri, Hicham Ouchitachen, Hicham Mouncif},
TITLE = {Clustering in Sensor Networks Using Regional Hierarchical Optimization: A Hybrid LEACH-ACO-GA Approach},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/cmc/online/detail/26517},
ISSN = {1546-2226},
ABSTRACT = {This study introduces a hybrid routing protocol, Low Energy Adaptive Clustering Hierarchy—Ant Colony Optimization—Genetic Algorithm (LEACH-ACO-GA), for wireless sensor networks. It combines regional ant colony optimization for cluster head selection with inter-cluster routing based on a genetic algorithm. The proposed method reduces energy consumption from 6.9 J (LEACH Classic) to 5.6 J (LEACH-ACO-GA) and decreases latency from 460 to 390 ms, while maintaining a packet delivery ratio of 0.97. These values are averaged over 70 rounds based on 30 independent simulation runs conducted on networks with 50 and 200 nodes. The hybrid method extends network lifetime by up to 50% compared to traditional LEACH and improves performance robustness in dense network environments. The results indicate that two-level metaheuristic optimization is effective for scalable and energy-efficient wireless sensor networks in Internet of Things scenarios.},
DOI = {10.32604/cmc.2026.075234}
}