L'evy flight particle swarm optimization (LFPSO)

Particle Swarm Optimization (PSO) is a stochastic strategy used to solve complicated nonlinear optimization problems. But, like other swarm intelligence based algorithms, it also suffers from slow convergence and stagnation problems. These problems cause disproportion in the exploration and exploitation capabilities of the algorithms. Thus to make equilibrium between diversity and convergence, a strategy named L;evy Flight PSO (LFPSO) is developed. In the proposed strategy, a l'evy flight random walk inspired local search approach is hybridized with PSO. Further, it is shown that the proposed strategy provides competitive solutions as compared to standard PSO 2011 algorithm when tested on 10 well known benchmark problems.