Dogukan TeberEfekan Zafer EnginDindar ÖzEngin, Efekan ZaferTeber, DogukanOz, Dindar2025-10-062023979835030659010.1109/ASYU58738.2023.102965892-s2.0-85178313592https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178313592&doi=10.1109%2FASYU58738.2023.10296589&partnerID=40&md5=c0f5fe0608d88a7948beb65a020e4d21https://gcris.yasar.edu.tr/handle/123456789/8516https://doi.org/10.1109/ASYU58738.2023.10296589Wireless Sensor Networks (WSNs) have vital applications in diverse domains including military environmental monitoring disaster management and security systems. Achieving both m-connectivity and k-coverage is critical for ensuring network reliability and effective area monitoring. In this study we propose a Hybrid Genetic Algorithm for Wireless Sensor Network deployment (HGA-WSN) that combines genetic algorithms with problem-specific local search to efficiently explore solutions. The paper compares HGA-WSN against a standard genetic algorithm a greedy heuristic and a standard simulated annealing implementation. The experiments encompass various problem instances considering different $\mathrm{m}\mathrm{k}$ and target count values. The results validate HGA-WSN's superior performance in terms of sensor count reduction. The algorithm's efficacy in optimizing WSN deployment across diverse applications is evident from its rapid convergence and enhanced connectivity and coverage achievements. © 2023 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessHga-wsn, Hybrid Genetic Algorithm, K-coverage, Local Search Strategies, M-connectivity, Optimization, Wireless Sensor Networks, Wsn Deployment, Disaster Prevention, Disasters, Environmental Management, Genetic Algorithms, Military Applications, Simulated Annealing, Diverse Domains, Hybrid Genetic Algorithm For Wireless Sensor Network Deployment, Hybrid Genetic Algorithms, K-coverage, Local Search Strategy, M-connectivity, Optimisations, Wireless Sensor Network Deployment, Wireless Sensor NetworksDisaster prevention, Disasters, Environmental management, Genetic algorithms, Military applications, Simulated annealing, Diverse domains, Hybrid genetic algorithm for wireless sensor network deployment, Hybrid genetic algorithms, K-coverage, Local search strategy, M-connectivity, Optimisations, Wireless sensor network deployment, Wireless sensor networksHybrid Genetic AlgorithmWireless Sensor NetworksOptimizationLocal Search StrategiesK-coverageWSN DeploymentM-connectivityHGA-WSNConference Object