A Mobile Tourist Decision Support System for Small Footprint Devices

This paper presents a mobile tourist decision support system that suggests personal trips, tailored to the user's interests and context. The system enables planning a customised trip that maximises the interest of the tourist, while taking the opening hours of the points of interest (POI) and the available time into account. The planning problem is modelled as an orienteering problem with time windows, which is a hard combinatorial optimisation problem. It is solved by an iterated local search metaheuristic procedure, resulting in a personal trip. This procedure is implemented and tested on a mobile phone. Despite the limited computational resources of a small footprint device, the system succesfully solves instances up to 50 POIs in an acceptable execution time. Not more than 1% of the solution quality turned out to be sacrificed in order to keep the worst---case execution time under 5 seconds.