Currently, metaheuristics are algorithms applied to solve various optimization problems. In this context, the Ant Lion Optimizer (ALO) algorithm is proposed in 2015 based on the ant lion hunting mechanism, where its main prey is the ants. The ALO has basically four steps: trapping the ants, random walk of the ants, elitism and catching preys. However, ALO presents problems in diversifying its population, which ends up decreasing its performance in certain problems. Thus, this work presents an improved ALO algorithm based on vector projection and called IALO (Improvement ALO). For comparison between the proposed algorithm and ALO, simulations are performed on 19 benchmark functions. The results obtained indicate that IALO is more efficient and robust than ALO for most benchmark functions.
