  This article presents a new algorithm which is a modified version of the
elite ant system (EAS) algorithm. The new version utilizes an effective
criterion for escaping from the local optimum points. In contrast to the
classical EAC algorithms, the proposed algorithm uses only a global updating,
which will increase pheromone on the edges of the best (i.e. the shortest)
route and will at the same time decrease the amount of pheromone on the edges
of the worst (i.e. the longest) route. In order to assess the efficiency of the
new algorithm, some standard traveling salesman problems (TSPs) were studied
and their results were compared with classical EAC and other well-known
meta-heuristic algorithms. The results indicate that the proposed algorithm has
been able to improve the efficiency of the algorithms in all instances and it
is competitive with other algorithms.
