New Firefly Algorithm based On Multi swarm & Learning Automata in Dynamic Environments
نویسندگان
چکیده
—Many real world problems are mostly time varying optimization problems, which require special mechanisms to detect changes in environment and then response to them. In this paper, combination of learning automata and firefly algorithm in order to improve the performance of firefly algorithm in dynamic environments has been proposed. In the algorithm, the firefly algorithm has been equipped with three learning automatons and velocity parameter, so they can increase diversity in response the dynamic environments. The main idea is based to split the population of fireflies into a set of interacting swarms. This Algorithm evaluated on a variety of instances of the multimodal dynamic moving peaks benchmark. Results are also compared with alternative approaches from the literature. They show that the new algorithm optimizer significantly outperforms previous approaches. Keywords-component; Dynamic Environment; Learning Automata; Multi Swarm; optimization methods & firefly Algorithm
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