\r\nhave been widely used since two decades. In most of the literature,

\r\nan ant is a constructive heuristic able to build a solution from scratch.

\r\nHowever, other types of ant algorithms have recently emerged: the

\r\ndiscussion is thus not limited by the common framework of the

\r\nconstructive ant algorithms. Generally, at each generation of an ant

\r\nalgorithm, each ant builds a solution step by step by adding an

\r\nelement to it. Each choice is based on the greedy force (also called the

\r\nvisibility, the short term profit or the heuristic information) and the

\r\ntrail system (central memory which collects historical information of

\r\nthe search process). Usually, all the ants of the population have the

\r\nsame characteristics and behaviors. In contrast in this paper, a new

\r\ntype of ant metaheuristic is proposed, namely SMART (for Solution

\r\nMethods with Ants Running by Types). It relies on the use of different

\r\npopulation of ants, where each population has its own personality.", "references": null, "publisher": "World Academy of Science, Engineering and Technology", "index": "International Science Index 109, 2016" }