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Hybrid Firefly Algorithm and Sperm Swarm Optimization Alg...
Rehannara Beegum T, Mohd Yamani Idna Idris, Mohamad Nizam Bin Ay · 2025-02-03 · via cs.NE updates on arXiv.org

This paper proposes a new hybrid algorithm, combining FA, SSO, and the N-R method to accelerate convergence towards global optima, named the Hybrid Firefly Algorithm and Sperm Swarm Optimization with Newton-Raphson (HFASSON). The performance of HFASSON is evaluated using 23 benchmark functions from the CEC 2017 suite, tested in 30, 50, and 100 dimensions. A statistical comparison is performed to assess the effectiveness of HFASSON against FA, SSO, HFASSO, and five hybrid algorithms: Water Cycle Moth Flame Optimization (WCMFO), Hybrid Particle Swarm Optimization and Genetic Algorithm (HPSOGA), Hybrid Sperm Swarm Optimization and Gravitational Search Algorithm (HSSOGSA), Grey Wolf and Cuckoo Search Algorithm (GWOCS), and Hybrid Firefly Genetic Algorithm (FAGA). Results from the Friedman rank test show the superior performance of HFASSON. Additionally, HFASSON is applied to Cognitive Radio Vehicular Ad-hoc Networks (CR-VANET), outperforming basic CR-VANET in spectrum utilization. These findings demonstrate HFASSON's efficiency in wireless network applications.

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