A Development of Travel Itinerary Planning Application using Traveling Salesman Problem and K-Means Clustering Approach

Abstract

In this paper, an algorithm for making travel itinerary using traveling salesman problem (TSP) and k-means clustering technique is proposed. We employ the algorithm to develop a web based application that can help travelers to plan their travel itinerary. The developed application should be able to provide an optimal itinerary recommendation in terms of distance and travel time. We use initial assumption that the traveler has determined all the tourist destinations he/she wants to visit and also the number of days he/she will stay in the region. Our approach consists of two steps, macro grouping using k-means and micro tour arrangement using TSP. Yogyakarta city, one of the tourist city in Indonesia, is used as an example to illustrate how the proposed algorithm can help travelers make their itinerary. This approach works well in small to medium number points of interest. However, the application still need many improvements such as to make it run faster and to handle the additional constraints that exist when creating an itinerary.