Smart Travel Itinerary Planning Application using Held-Karp Algorithm and Balanced Clustering Approach

In this paper, a mobile application that could assist tourists in arranging travel itineraries has been developed. In the case of making an itinerary, often tourists have been determined the tourist destinations they want to visit, but they confused in determining the order of efficient visits. Balanced clustering is an approach to classify tourist destinations based on the proximity of their location, which gives the results of a cluster whose cardinality between members of the cluster is balanced. Furthermore, each cluster group from the results of this clustering will be seen as a case of the Traveling Salesman Problem (TSP), which we need to find the most efficient sequence of visits in each cluster that contains a list of tourist destinations. The algorithm used for the completion of the TSP is the Held-Karp algorithm. From the running time measurement test, it is obtained that the Held-Karp algorithm solves the problem of finding the TSP route faster than using the Brute Force approach. In addition, the implementation of balanced clustering using the Hungarian algorithm can make the number of tourist destinations to be visited in each day become balance.