Ant Algorithm Modification

Ant Algorithm is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristic, like evolutionary methods, Ant Algorithms often show good optimization behavior but are slow when compared to classical heuristics. This problem happened due to the large number of control parameters used. Those parameters, that produce best performance, may be selected hand -tuned or using a systematic procedure. In this paper, we discuss how to evolve the ant algorithm by reducing the number of those parameters and improve their performance. This modification result in speeding up ant algorithm compared to classical one. A simple implementation of this approach tested on the traveling salesman problem (TSP) and many other problems. The results show that the modified ant algorithms have good performance compared to the original Ant Algorithm.