Firefly Algorithm for Swarm Intelligence Clustering Method
Sung-Soo Kim, Bum-Su Kang · Journal of Korean Institute of Industrial Engineers · 2019
Swarm Intelligence (SI) is a kind of artificial intelligence (AI) discipline that is popular in these days. Firefly algorithm (FA) is recently developed for new SI. The objective of this paper is to propose the FA to find the optimal data clustering solution with number of clusters. Our proposed FA is suitable for highly nonlinear and multimodal optimization because FA can consider the attractiveness and distance between the fireflies (solutions) simultaneously. We use the silhouette as valid index to evaluate the solution with number of clusters considering the intra-cluster and inter-cluster distance at the same time. We also use the relative distance rate (VSUBj/SUB) of each data j which is used to generate the good initial solutions to save the much computation time for silhouette evaluations. The performance of our proposed FA using silhouette with relative distance rate is validated using several real data sets by experiment and analysis.