Aigaion: RACTI / RU1 Technical Report Series (Web Based)

[RACTI-RU1-2014-35] Gavalas, Damianos, Kasapakis, Vlasios, Konstantopoulos, Charalampos, Pantziou, Grammati, Vathis, Nikolaos and Zaroliagis, Christos, A Personalized Multimodal Tourist Tour Planner, in: 13th International Conference on Mobile and Ubiquitous Multimedia, pages 73-80, MUM 2014 (ACM), 2014.

Keywords:

Tourist Trip Design Problem, Multimodal Route Planning, Orienteering Problem, Context Awareness, Mobile Application

[RACTI-RU1-2014-15] Gavalas, Damianos, Konstantopoulos, Charalampos, Mastakas, Konstantinos and Pantziou, Grammati, Mobile Recommender Systems in Tourism, in: Journal of Network and Computer Applications, volume 39, pages 319-333, 2014.

Keywords:

Mobile tourism, Mobile recommender systems, Personalization; Points of interest; Pull-based, Reactive, Proactive, Location awareness, Context-awareness, Route planning, Tour planning

[RACTI-RU1-2014-8] Gavalas, Damianos, Konstantopoulos, Charalampos, Mastakas, Konstantinos, Pantziou, Grammati and Vathis, Nikolaos, Efficient Heuristics for the Time Dependent Team Orienteering Problem with Time Windows, in: International Conference on Applied Algorithms - ICAA’2014, pages 151-162, Springer-Verlag, 2014.
Abstract: 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 transport. The main objective of this problem is to select POIs that match tourist preferences, while taking into account a multitude of parameters and constraints and respecting the time available for sightseeing in a daily basis. 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 service schedules. Herein, we propose two 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 included the metropolitan transit network and real POI sets compiled from Athens (Greece).