Immune Multi-population Firefly Algorithm and Its Application in Multimodal Function Optimization

In this paper, a novel immune multl-populanon firefly algorithm (IMPFA) is presented to solve multimodal function optlmlzatton 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 multl-populatten learnmg mechanism is used to search globally in the feasible region, and then the NUM CSA is utilized to search locally for improving the accuracy of the sub-optlmal solutions obtained with MPFA. Simulation results show that the IMPFA is extremely effective and increases the precision of solutions.