Optimization approaches to support the planning and analysis of travel itineraries

This paper addresses the problem of elaborating travel itineraries considering the visitors´ profiles, travel distances and costs. Other parameters such as how much the tourists value the attractions offered are particularly taken into account, as well as their preferences regarding the order of visiting these attractions. This problem can be seen as a traveling salesman problem with profits that also considers priority prizes. It is described by an optimization model based on mixed integer programming, which aims to generate itineraries that maximize the total value of the attractions visited and minimize the total travel cost involved. We present results for sets of instances based on randomly generated and real data by applying mathematical programming techniques and a tailored tabu search algorithm. To obtain the input parameters of the problem for the real cases, some statistical techniques are used to analyze the data collected, such as multivariate correspondence analysis. The resulting solutions illustrate the potential application of the proposed approach to support planning and formatting decisions of travel itineraries.