Hybrid ant colony system and flower pollination algorithms for global optimization

Nature is one of the best sources for inspiration to solve problems, and therefore, several nature inspired algorithms have been proposed. One of these algorithms is the ant colony system which is based on the behaviour of real ant colony. The ant colony system algorithm is one of the best variants of the ant colony optimization algorithm. However, the exploration mechanism in ant colony system is not efficient, specifically when the problem instance increases. A hybrid algorithm between ant colony system and flower pollination algorithm for optimization problems is proposed. Two approaches which are based on the level of hybridization, namely low level hybridization and high level hybridization, are used in developing the hybrid algorithms. The approaches are based on the generic structures of different hybridization levels.