The document describes the Salp Swarm Algorithm (SSA), a bio-inspired optimization algorithm. SSA mimics the behavior of salp swarms in oceans. Salps move in chains and the leader salp guides the followers. The algorithm models this with the leader salp moving towards food sources using equations that balance exploration and exploitation, while follower salps move based on the leader's position. The document provides pseudocode and an example of applying SSA to optimize a benchmark function. It also notes that SSA is not well-suited for multi-objective optimization problems since it only tracks a single best solution.