ALO-DM: A Smart Approach Based on Ant Lion Optimizer with Differential Mutation Operator in Big Data Analytics

The ant lion optimizer (ALO) is a novel swarm intelligence optimization algorithm, but its population diversity and convergence precision can be limited in some applications. In this paper, we proposed an approach based on ALO and differential mutation operator that called ALO-DM. In this method, differential mutation operator and greedy strategy enhance the diversity of the population. In addition, combining it with data mining algorithms can be useful and practical in big data analytics problems. The simulation results not only show that the ALO-DM is able to obtain accurate solution, but also demonstrate that it is feasible and effective.