This paper proposes genetic ant algorithm through the research of the traditional genetic algorithm and ant colony optimization. This algorithm use the results of the genetic algorithm to initialize the pheromone distribution, use its strong adaptability and rapid global convergence and then get the optimal solution through the colony algorithm that has parallelism, positive feedback system and good solution efficiency. The simulation results of 0-1 knapsack and QoS demonstrate that this algorithm has higher converging speed, stability and global optimization ability. © 2010 Published by Elsevier Ltd.
Zhang, W. G., & Lu, T. Y. (2012). The research of genetic ant colony algorithm and its application. In Procedia Engineering (Vol. 37, pp. 101–106). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2012.04.210