A Mobile Tourist Decision Support System for Small Footprint Devices

Authors:
Wouter Souffiau;Joris Maervoet;Pieter Vansteenwegen;Greet Berghe;Dirk Oudheusden
Affiliations:
KaHo St.-Lieven, Information Technology, Ghent, Belgium 9000 and Centre for Industrial Management, Katholieke Universiteit Leuven, Leuven (Heverlee), Belgium 3001;KaHo St.-Lieven, Information Technology, Ghent, Belgium 9000;Centre for Industrial Management, Katholieke Universiteit Leuven, Leuven (Heverlee), Belgium 3001;KaHo St.-Lieven, Information Technology, Ghent, Belgium 9000;Centre for Industrial Management, Katholieke Universiteit Leuven, Leuven (Heverlee), Belgium 3001
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

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.