Energy efficiency remains a critical challenge in Wireless Sensor Networks (WSNs) due to the limited power of sensors, necessitating effective energy consumption management to prolong network lifespan. Furthermore, dynamic topology changes caused by sensor mobility or failure complicate routing and data transmission, highlighting the need for robust optimization methods. Metaheuristic optimization has emerged as a promising approach for developing algorithms to address these challenges and enhance WSN performance. This study systematically reviews recent advancements (2019-2024) in metaheuristic optimization methods applied to WSNs. A literature search was conducted using IEEE Xplore, Springer, Scopus, and Science Direct, adhering to PRISMA guidelines to ensure methodological rigor. The review identified 32 relevant studies that examine optimization algorithms for improving energy efficiency, routing, and data transmission in WSNs. The findings underscore the effectiveness of metaheuristic approaches in addressing key challenges in WSNs while identifying research gaps. Future work should prioritize the development of innovative metaheuristic algorithms to overcome energy constraints and further optimize network efficiency. © 2025 IEEE.