Heuristics for the time dependent team orienteering problem: Application to tourist route planning

The Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) can be used to model several real life problems. Among them, the route planning problem for tourists interested in visiting multiple points of interest (POIs) using public transportation. The main objective of this problem is to select POIs that match tourist preferences, taking into account a multitude of parameters and constraints while respecting the time available for sightseeing in a daily basis and integrating public transportation to travel between POIs (Tourist Trip Design Problem, TTDP). TDTOPTW is NP-hard while almost the whole body of the related literature addresses the non-time dependent version of the problem. The only TDTOPTW heuristic proposed so far is based on the assumption of periodic transit service schedules. Herein, we propose efficient cluster-based heuristics for the TDTOPTW which yield high quality solutions, take into account time dependency in calculating travel times between POIs and make no assumption on periodic service schedules. The validation scenario for our prototyped algorithms involved the transit network and real POI datasets compiled from the metropolitan area of Athens (Greece). Our TTDP algorithms handle arbitrary (i.e. determined at query time) rather than fixed start/end locations for derived tourist itineraries. •Tourist Trip Design Problem (TTDP): near-optimal multiple-day tourist tours maximizing tourist satisfaction (profit).•Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW): Modeling TTDP incorporating public transit transfers.•First heuristic algorithms incorporating time dependency (with no assumption on periodicity) in travel costs.•The start/end locations of any route are arbitrarily defined within the tourist destination area, at runtime.•Testing on new TTDP-tailored benchmark instances based on POIs and the public transit network of Athens, Greece.