Shuffled frog-leaping algorithm (SFLA) is a recent addition to the family of stochastic search
methods that mimic the social and natural behavior of species. SFLA combines the
advantages of local search process of particle swarm optimization (PSO) and mixing of
information of the shuffled complex evolution. The basic idea behind modeling of such
algorithms is to achieve near to global solutions to the large-scale optimization problems
and complex problems which cannot be solved using deterministic or traditional numerical …