ABSTRACT
WSA is a new bio-inspired heuristic optimization algorithm that imitates the way wolves search for food and survive by avoiding their enemies. The WSA was proposed by Rui Tang et al. [1].
Wolves are social predators that hunt in packs. Wolves typically commute as a nuclear family. They remain silent and use stealth when hunting prey together and have developed unique, semi-cooperative characteristics; that is, they move in a group in a loosely coupled formation, but tend to take down prey individually [1]. WSA naturally balances scouting the problem space in random groups (breadth) and searching for the solution individually (depth).
