Immune Multi-Population Firefly Algorithm and its Application in Multimodal Function Optimization

In this paper, a novel immune multi-population firefly algorithm (IMPFA)is presented to solve multimodal function optimization problems. The proposed algorithm integrates multi-population firefly algorithm (MPFA)with non-uniform mutation clonal selection algorithm (NUMCSA). In each loop iteration, firstly, the MPFA based on multi-population learning mechanism is used to search globally in the feasible region, and then the NUMCSA is utilized to search locally for improving the accuracy of the sub-optimal solutions obtained with MPFA. Simulation results show that the IMPFA is extremely effective and increases the precision of solutions.