부산대학교 도서관

Various methods have been proposed to solve the traveling salesman problem, referred to as the TSP. In order to solve the TSP, the cost metric (e.g., the travel time and distance) between nodes is needed. As we do not always have specific criterion for the cost metric we are proposing using a new computation environment that is used all over the world—Google Maps. We think a cost metric obtained from Google maps is a good, impartial value with little room for variation, making it easier and more efficient to make map information visible. Moreover, a scalable computation environment can be prepared by using cloud computing technology. We can even expand the TSP and calculate routes taken by multiple people. The numerical results show this computation environment to be effective.