MFASA: A New Memetic Firefly Algorithm Based on Simulated Annealing

Firefly algorithm is a global optimization algorithm. Unlike other algorithms such as genetic algorithm and particle swarm optimization algorithm, it benefits a competitive potential. However, it fails in finding global optimization solution for some cases. This paper introduces a new hybrid algorithm based on a simulated annealing algorithm to improve the functionality of the firefly algorithm. The simulated annealing algorithm is a algorithm with remarkable local search ability. Simultaneous application of the firefly algorithm and simulated annealing algorithm enables us to effectively benefit from the global search and local search capacity of those algorithms. To test the efficiency of the proposed method, five benchmark functions were examined. The results proved that the suggested method provides a competitive efficiency compared to other methods

کلیدواژه ها:

simulated annealing algorithm ، metaheuristic algorithm ، firefly algorithm ، global search ، local search