Ant algorithms are well-known metaheuristics which
have been widely used since two decades. In most of the literature,
an ant is a constructive heuristic able to build a solution from scratch.
However, other types of ant algorithms have recently emerged: the
discussion is thus not limited by the common framework of the
constructive ant algorithms. Generally, at each generation of an ant
algorithm, each ant builds a solution step by step by adding an
element to it. Each choice is based on the greedy force (also called the
visibility, the short term profit or the heuristic information) and the
trail system (central memory which collects historical information of
the search process). Usually, all the ants of the population have the
same characteristics and behaviors. In contrast in this paper, a new
type of ant metaheuristic is proposed, namely SMART (for Solution
Methods with Ants Running by Types). It relies on the use of different
population of ants, where each population has its own personality.