Ant colony algorithm-based travelling route problems: A case study in Bangkok

Ant Colony Optimization (ACO) is a new heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization problems such as the traveling salesman problem, the vehicle routing problem and the job shop scheduling problem. The inspiring source of ACO is the pheromone trail laying and following behavior of real ants, which use pheromones as a communication medium. In this research, ant colony algorithm-based travelling route problem is proposed. The objective is to develop the model to find the optimal route by using ACO algorithm, Bangkok area, Thailand is used for a case study. The various connecting cities in Thailand with appropriate distances are identified and created for running experiments. This research involves formulating and applying the ACO algorithms to find the shortest path based on the distance calculated from source to destination places. The system is implemented and running examples can be shown in this research. Finally, a graphical user interface has been developed to provide display and manipulation of the algorithm including calculation of cost based on the distance traveled.