Current Studies and Applications of Shuffled Frog Leaping Algorithm: A Review

Shuffled Frog Leaping Algorithm (SFLA) is one of the most widespread algorithms. It was developed by Eusuff and Lansey in 2006. SFLA a population-based metaheuristic algorithm that combines benefits memetics with particle swarm optimization. has been used various areas, especially engineering problems due to its implementation easiness limited variables. Many improvements have made alleviate drawbacks, whether they were achieved through modifications or hybridizations other well-known This paper reviews relevant works on this algorithm. An overview first conducted, followed algorithm's recent hybridizations. Next, applications are discussed. Then, an operational framework SLFA variants proposed analyze their uses different cohorts applications. Finally, future suggested. The main incentive conduct survey provide useful information about researchers interested working enhancement application.