Moderate ant system: An improved algorithm for solving TSP
Ping Guo, Zhujin Liu · 2011
Ant Colony Optimization algorithms often suffer from criticism for the local optimization and premature convergence. In this paper, we introduce several main ant algorithms, analyze their design ideas, and draw the conclusion that biases in transition rules and update rules are the root cause of the local optimization and premature convergence. Inspired by the adaptive behaviors of some Monomorium ant species in the real world, we design a novel transition rule to overcome the existing problems of ACO algorithms. Moreover, applying the new transition rule, we propose an improved version of Ant System-Moderate Ant System. This improved algorithm is experimentally turned out to be effective and competitive.