id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ejpam-7030	El-Shorbagy, M.A.; Nasar, Islam	Salp Swarm Optimization: A Comprehensive Review of Recent Advances, Variants, Applications, and Future Research Directions	2025	30	.pdf	application/pdf	11570	722	43	Future Research Directions While various Salp Swarm Algorithm (SSA) variants, including Chaotic SSA (CSSA), Quantum-inspired SSA (QSSA), and Adaptive SSA (ASSA), have demonstrated significant improvements, multiple opportunities remain for further research and development: • Hybridisation with Other Metaheuristics: Integrating SSA variants with com- plementary Optimization methods, such as Differential Evolution, Particle Swarm Optimization, or Genetic Algorithms, has the potential to enhance convergence speed and solution quality, particularly in high-dimensional and multimodal contexts. • Rigorous Benchmarking and Comparative Analysis: Future studies should prioritise systematic benchmarking of SSA variants against classical metaheuristics M. A. El-Shorbagy, I. Nassar / Eur.	cache/ejpam-7030.pdf	txt/ejpam-7030.txt