Multi-colony ant algorithms for the dynamic travelling salesman problem - Mavrovouniotis, Michalis; Yang, Shengxiang; Yao, Xin (My University, 2014)
A multi-colony ant colony optimization (ACO) algorithm consists of several colonies of ants. Each colony uses a separate pheromone table in an attempt to maximize the search area explored. Over the years, multi-colony ACO algorithms have been successfully applied on different optimization problems with stationary environments. In this paper, we investigate their performance in dynamic environments. Two types of algorithms are proposed: homogeneous and heterogeneous approaches, where colonies share the same properties and colonies have their own (different) properties, respectively. Experimental results on the dynamic travelling salesman problem show that multi-colony ACO algorithms have promising performance in dynamic environments when compared with single colony ACO algorithms.
Keywords: Ant colony optimization; Artificial intelligence; ACO algorithms; Ant Colony Optimization algorithms; Dynamic environments; Multi-colony ant algorithms; Optimization problems; Search area; Stationary environments; Travelling salesman problem; Traveling salesman problem