Volume 9 • Issue 1 • PP: 53–60 • 2025
Nature-Inspired Metaheuristic Optimization for Network Design and Communication Systems: Trends, Applications, and Future Directions
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© 2025 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Communication network design (CND) and wireless sensor networks (WSNs) present significant challenges, particularly in optimizing network reliability, energy efficiency, and cost-effectiveness. This literature review discusses the use of metaheuristic algorithms to solve these 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 such as vehicular ad-hoc networks (VANETs) and Internet of Things (IoT)-enabled WSNs. The review also discusses applications to 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, this review calls for increased use of metaheuristic techniques to further the application of future networks in smart cities, healthcare, and secure network architectures.
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