Planning the trip itinerary for tourist groups

Sightseeing trips are often done in groups, where tourists enjoy their trip in company with their relatives or friends. Therefore, in this paper, in order to model the case of trips for tourist groups, we introduce a new problem, as an extension of the existing problem in the literature that is used for planning the trip of a single tourist. The new problem extends the existing problem with two additional concepts. The first is the consideration of multiple tourists, where their individual preferences about points of interests are taken into account, and the second is the introduction of the concept of mutual social relationship between the different tourists. For the actual single tourist trip problem, we use an algorithm that obtains comparable results with the state of the art algorithms, whereas for the group trip problem, since no solution has been published before, we design a new algorithm based on tabu search metaheuristic that uses two new unique operators for exploring the search space. As a result, this paper proposes an anytime algorithm that in average takes about 20 s to obtain better personalized itineraries for tourist groups than when scheduling the whole group together.