A Novel Hybrid Firefly Algorithm for Global Optimization

Firefly algorithm is a new optimization technique based on swarm intelligence. It simulates the social behavior of fireflies. The search pattern of firefly algorithm is determined by the attractions among fireflies, whereby a less bright firefly moves toward a brighter firefly. In firefly algorithm, each firefly can be attracted by all other brighter fireflies in the population. But firefly algorithm is similar to other swarm intelligence algorithms; the performance of firefly algorithm is poor in high dimensional problems. It has low local search accuracy and is easy to fall into local extremum in some case. To overcome these problems, the quantum theory and mutation operation was used to improve firefly algorithm, a quantum-inspired hybrid firefly algorithm was proposed. In proposed algorithm, each quantum firefly can express two position of solution space, location update is implemented by quantum gate calculation, the mutation operation is used to jump out of the local extremum. Optimization Experiments are conducted using well-known benchmark functions. The results show that the proposed algorithm can efficiently improve the global search capability and the accuracy of solutions.