The Travelling Salesman Problem (TSP) is one of the best known NP-hard problems, which means that there is not guaranteed to get the optimal route and no exact algorithm to solve it in polynomial time. The method which would definitely obtain the optimal solution of TSP is the method of exhaustive enumeration and evaluation. This procedure begins by generating the possibility of all the tours and evaluate according length of the tour. The tour with the smallest length chosen as the best, and guaranteed to be optimal. At this time many companies and institutions are confronted and have to resolve cases of TSP. For example, delivery service companies that every day faced with the problems, it occurs because the route followed to get to the destination is not optimal. Examples of cases in delivery service, a courier needs to deliver goods to some customers with a different destinations. Therefore, time is of considerable concern in the delivery of goods it relates to the reputation of the company. To reach these goals required a system capable of providing an optimal travel route so that the travel time to be minimum. So it needs an application that can optimize the TSP solution, it uses a genetic algorithm to produce the optimal solution in a short time.
This project implements search-based algorithms that always yield an optimal path if one exists. Path finding algorithms, such as breadth-first search (BFS), Dijkstra, and A*, have been used find an optimal path for the salesman from the user-defined start to end point.