A fuzzy GRASP for the tourist trip design with clustered POIs

Abstract In tourist sector, expert and intelligent systems should perform at least two main tasks or services: point of interest recommendation and route generation. In this regard, the personalized electronic tourist guide, generally implemented on hand-held device, such as mobile applications or in web. These tools must work like an expert and intelligent system that perform the services mentioned above then they should need low computation effort. In this paper we focus on the route generation based on scores of the points of interest and the distance or time between them. We consider a new extension of the Tourist Trip Design Problem, named Tourist Trip Design Problem with Clustered Points of Interest, where points of interest are grouped in clusters representing different types of attraction sites. Moreover, minimum/maximum limits are imposed on the number of points of interest belonging to the each clusters that are visited in the same route. Since it is a novel problem, we generate two sets of instances in order to evaluate the accuracy of our solution approach. A Fuzzy GRASP (Greedy Randomized Adaptive Search Procedure), in which both distance based and score based evaluation criteria are used to guide the candidates selection in the construction phase is proposed. The results provided by our heuristic are compared with those obtained by solving the MIP formulation. Computational results carried out on real and real-like instances show the effectiveness and efficiency of the proposed approach and its suitability to be part of a Personalized Electronic Tourist Guide in hand-held devices.

[1]  Alain Hertz,et al.  The capacitated team orienteering and profitable tour problems , 2007, J. Oper. Res. Soc..

[2]  Charalampos Konstantopoulos,et al.  A survey on algorithmic approaches for solving tourist trip design problems , 2014, Journal of Heuristics.

[3]  Alberto Belussi,et al.  Adaptive Trip Recommendation System: Balancing Travelers among POIs with MapReduce , 2018, 2018 IEEE International Congress on Big Data (BigData Congress).

[4]  Charalampos Konstantopoulos,et al.  Efficient Heuristics for the Time Dependent Team Orienteering Problem with Time Windows , 2014, ICAA.

[5]  Olatz Arbelaitz,et al.  Evaluation of Intelligent Routes for Personalised Electronic Tourist Guides , 2012, ENTER.

[6]  David R. Karger,et al.  Approximation Algorithms for Orienteering and Discounted-Reward TSP , 2007, SIAM J. Comput..

[7]  Alain Hertz,et al.  Metaheuristics for the team orienteering problem , 2005, J. Heuristics.

[8]  Shih-Wei Lin,et al.  A simulated annealing heuristic for the team orienteering problem with time windows , 2012, Eur. J. Oper. Res..

[9]  Bruce L. Golden,et al.  The team orienteering problem , 1996 .

[10]  Richard F. Hartl,et al.  Heuristics for the multi-period orienteering problem with multiple time windows , 2010, Comput. Oper. Res..

[11]  Jürgen Dorn,et al.  A Tabu Search approach for Multi Constrained Team Orienteering Problem and its application in touristic trip planning , 2012, 2012 12th International Conference on Hybrid Intelligent Systems (HIS).

[12]  Charalampos Konstantopoulos,et al.  Heuristics for the time dependent team orienteering problem: Application to tourist route planning , 2015, Comput. Oper. Res..

[13]  Nacima Labadie,et al.  The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search , 2012, Eur. J. Oper. Res..

[14]  Olatz Arbelaitz,et al.  Integrating public transportation in personalised electronic tourist guides , 2013, Comput. Oper. Res..

[15]  Roberto Montemanni,et al.  An ant colony system for team orienteering problems with time windows , 2023, 2305.07305.

[16]  Michel Gendreau,et al.  An exact algorithm for team orienteering problems , 2007, 4OR.

[17]  Mauro Birattari,et al.  Tuning Metaheuristics - A Machine Learning Perspective , 2009, Studies in Computational Intelligence.

[18]  Dirk Van Oudheusden,et al.  The City Trip Planner: An expert system for tourists , 2011, Expert Syst. Appl..

[19]  Lixin Tang,et al.  Iterated local search algorithm based on very large-scale neighborhood for prize-collecting vehicle routing problem , 2006 .

[20]  Steven E. Butt,et al.  An optimal solution procedure for the multiple tour maximum collection problem using column generation , 1999, Comput. Oper. Res..

[21]  El-Ghazali Talbi,et al.  Metaheuristics - From Design to Implementation , 2009 .

[22]  Celso C. Ribeiro,et al.  Optimization by GRASP: Greedy Randomized Adaptive Search Procedures , 2016 .

[23]  Duc-Cuong Dang,et al.  A memetic algorithm for the team orienteering problem , 2008, 4OR.

[24]  Daniele Vigo,et al.  Vehicle Routing Problems with Profits , 2014, Vehicle Routing.

[25]  José Andrés Moreno Pérez,et al.  Fuzzy Constructive Heuristics , 2003 .

[26]  Katerina Kabassi,et al.  Personalizing recommendations for tourists , 2010, Telematics Informatics.

[27]  Sarah S. Lam,et al.  Discrete particle swarm optimization for the team orienteering problem , 2011, Memetic Comput..

[28]  Dirk Van Oudheusden,et al.  The Mobile Tourist Guide: An OR Opportunity , 2007, OR Insight.

[29]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[30]  Dirk Van Oudheusden,et al.  The Multiconstraint Team Orienteering Problem with Multiple Time Windows , 2010, Transp. Sci..

[31]  Dirk Van Oudheusden,et al.  Iterated local search for the team orienteering problem with time windows , 2009, Comput. Oper. Res..

[32]  Arenberg Doctoral,et al.  Automated Tourist Decision Support , 2010 .

[33]  Olatz Arbelaitz,et al.  Intelligent Routing System for a Personalised Electronic Tourist Guide , 2009, ENTER.

[34]  M. Friedman The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance , 1937 .

[35]  Elise Miller-Hooks,et al.  A TABU search heuristic for the team orienteering problem , 2005, Comput. Oper. Res..

[36]  D. Gavalas,et al.  Web application for recommending personalised mobile tourist routes , 2012, IET Softw..

[37]  Tom M. Cavalier,et al.  A heuristic for the multiple tour maximum collection problem , 1994, Comput. Oper. Res..

[38]  Thibaut Vidal,et al.  Large Neighborhoods with Implicit Customer Selection for Vehicle Routing Problems with Profits , 2014, Transp. Sci..