Discovering the maximum k-clique on social networks using bat optimization algorithm

Abstract The k-clique problem is identifying the largest complete subgraph of size k on a network, and it has many applications in Social Network Analysis (SNA), coding theory, geometry, etc. Due to NP-Complete nature problem, meta-heuristic approaches have raised interest researchers some algorithms are developed. In this paper, new algorithm based Bat optimization approach developed for finding maximum social network increase convergence speed evaluation criteria such as Precision , Recall, F1-score . proposed simulated Matlab® software over Dolphin DIMACS dataset = 3, 4, 5. computational results show that former increased comparison with Genetic Algorithm (GA) Ant Colony Optimization (ACO) approaches. Besides, also modified latter obtained 100%