Salp Swarm Optimization: A critical review

In the crowded environment of bio-inspired population-based metaheuristics, Salp Swarm Optimization (SSO) algorithm recently appeared and immediately gained a lot momentum. Inspired by peculiar spatial arrangement salp colonies, which are displaced in long chains following leader, this seems to provide an interesting optimization performance. However, original work was characterized some conceptual mathematical flaws, influenced all ensuing papers on subject. manuscript, we perform critical review SSO, highlighting issues present literature their negative effects process carried out algorithm. We also propose mathematically correct version named Amended Optimizer (ASSO) that fixes discussed problems. benchmarked performance ASSO set tailored experiments, showing it is able achieve better results than SSO. Finally, performed extensive study aimed at understanding whether SSO its variants advantages compared other metaheuristics. The experimental results, where cannot outperform simple well-known suggest scientific community can safely abandon