ACOℝ-V - An algorithm that incorporates the visibility heuristic to the ACO in continuous domain

Ant Colony Optimization (ACO) is an optimization metaheuristic based on the foraging behavior of ants. This metaheuristic was originally proposed to find good solutions to discrete combinatorial problems. Many extensions of the ACO heuristic for continuous domain have been proposed, but even those that claim close similarity with classical (discrete domain) ACO, like ACOR, do not use the heuristic information called visibility, commonly used in the original ACO algorithm. In this paper, we show the importance of the visibility in ACO, by proposing ACO_ℝ-V , a variant of ACOR that performs better in a number of benchmark functions. Results from our experiments shown better solutions when comparing ACO_ℝ-V to original ACOR. Moreover, the visibility increased the convergence speed as it reduced the number of times the objective function must be evaluated for a given precision in the solution.