Volume 9 • Issue 1 • PP: 72-80 • 2025
Nature-Inspired Metaheuristic Optimization for Network Design and Communication Systems: Trends, Applications, and Future Directions
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Communication network design (CND) and wireless sensor networks (WSNs) presents significant challenges, particularly in optimizing network reliability, energy efficiency, and cost-effectiveness. This literature review discusses using metaheuristic algorithms to solve the mentioned NP-hard problems and provide accurate results for network reliability, resource management assignment, and energy utilization in data transmission networks. Recent advancements in hybrid metaheuristic approaches, such as combining Genetic Algorithms with Branch and Bound (GA-BB) or Particle Swarm Optimization with Simulated Annealing (PSO-SA), demonstrate their effectiveness in optimizing network performance in emerging domains like vehicular ad-hoc networks (VANETs) and Internet of Things (IoT)- enabled WSNs. The review also discusses the application of optimization approaches about distinct issues such as cluster head selection in WSNs, routing protocols in dynamic networks, and supply chain network design. These developments are essential in evolving technologies such as 6G networks and the Internet of Everything (IoE), where complex systems demand innovative optimization strategies. By highlighting these concerns in the current study, this review calls for the increased use of metaheuristic techniques towards furthering the application of future networks in smart cities, healthcare, and secure network architectures.
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References
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