Applying opposition-based ideas to the ant colony system

This paper presents several extensions to an algorithm in the family of Ant Colony Optimization, the Ant Colony System. The proposed extensions are based on the idea of opposition and attempt to increase the exploration efficiency of the solution space. The modifications focus on the solution construction phase of the ant colony system. Three of the proposed methods work by pairing the ants and synchronizing their path selection. The two other approaches modify the decisions of the ants by using an opposite-pheromone content. Results on the application of these algorithms on Travelling Salesman Problem instances demonstrate that the concept of opposition is not easily applied to the ant algorithm. Only one of the pheromone-based methods showed performance improvements that were statistically significant. The quality of the solutions increased and more optimal solutions were found. The other extensions showed no clear improvement. Further work must be conducted to explore the successful pheromone-based approach, as well as to determine if opposition should be applied to a different phase of the algorithm.