Extended firefly algorithm for multimodal optimization

摘要

Many real world optimization problems have to be treated as multi-objective optimization problems. The Firefly Algorithm (FFA), a stochastic optimization method mimics the behavior of fireflies, which use a kind of flashing light to communicate with other members of their species. FFA is implicitly able to detect good local solutions on its way to the best solution. This disposition is successfully boosted by identifying clusters of fireflies which gather around promising local solutions. Subsequently, the update rules used for finding the new positions of the fireflies are applied among members of the particular clusters only. This extended FFA will be used to solve the well known Rastrigin test function and an electromagnetic field problems, the optimal design of a magneto-rheologic clutch, respectively.