Ant Colony Optimization for Solving Traveling Salesman Problem

An ant colony capable of solving the traveling salesman problem (TSP). TSP is NP-hard problem. Even though the problem itself is simple, when the number of city is large, the search space will become extremely large and it becomes very difficult to find the optimal solution in a short time. One of the main ideas of ant algorithms is the indirect communication of a colony of agents, called (artificial) ants, based on pheromone trails (pheromones are also used by real ants for communication).The (artificial) pheromone trails are a kind of distributed numeric information which is modified by the ants to reflect their experience while solving a particular problem. Computer simulations demonstrate that the artificial ant colony is capable of generating good solutions to both symmetric and asymmetric instances of the TSP. The method is an example, like simulated annealing, neural networks, and evolutionary computation, of the successful use of a natural metaphor to design an optimization algorithm.