An Efficient Trip Planning Algorithm Under Constraints

The problem of trip planning has received wide concerns in recent years. More and more people require the service of automatically confirming the optimal tour route. When users assign the source and the destination, and the time limit of the tour, how can automatically decide the optimal tour route with the highest sum of the popularity scores of scenic spots. Current methods for trip planning are on the setting that providing with the route which is composed of the scenic spots to travel. These would work poorly for the pre-mentioned problem when the route satisfying the constraints can not be found. Thus we adjust the setting to giving the route composed of the scenic spots which users visit or simply pass by. Obviously, the modified problem would incur larger search cost as each scenic spot in the given route has two states. It can be demonstrated that this new problem is NP hard, making it difficult to find an efficient exact algorithm for the present. In this paper, we propose a greedy strategy based algorithm to solve the trip planning problem, and we also present an improved algorithm with better performance. The experimental results on synthesized and real data sets reveal that our algorithm is able to find the approximately optimal path in high efficiency.