Using a heuristic approach to design personalized urban tourism itineraries with hotel selection

Abstract Urban tourism is a worldwide form of tourism and is one of the most important social and economic impetus for urban development. The urban tourism market has been increasingly dominated by the demand for personalized experiences. Accordingly, this study aims to design personalized itineraries with hotel selection for multi-day urban tourists. A two-level heuristic approach is proposed, which embeds genetic algorithm, variable neighborhood search, and differential evolution algorithm into the structure of memetic algorithm. A case study in Xiamen, a coastal city in Southeast China, is carried out to evaluate the performance of our approach. Results of paired sample t-tests show that our proposed approach is remarkably superior to existing methods. In addition, compared with previous methods, our approach can design more reasonable and personalized itineraries for tourists.

[1]  Dimitris K. Tasoulis,et al.  A Review of Major Application Areas of Differential Evolution , 2008 .

[2]  Chang-Shing Lee,et al.  Ontological recommendation multi-agent for Tainan City travel , 2009, Expert Syst. Appl..

[3]  Mohamed Goaied,et al.  Determinants of Tunisian hotel profitability: The role of managerial efficiency , 2016 .

[4]  J.Christopher Holloway,et al.  The guided tour a sociological approach , 1981 .

[5]  Bob McKercher,et al.  Trip destinations, gateways and itineraries: the example of Hong Kong , 2002 .

[6]  Koorush Ziarati,et al.  A novel method for solving the orienteering problem with hotel selection , 2017, 2017 International Symposium on Computer Science and Software Engineering Conference (CSSE).

[7]  Milagros Vivel-Búa,et al.  Impact of location on profitability in the Spanish hotel sector , 2016 .

[8]  Ulrike Gretzel,et al.  Effects of podcast tours on tourist experiences in a national park , 2012 .

[9]  Yang Yang,et al.  Understanding Guest Satisfaction with Urban Hotel Location , 2018 .

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

[11]  Pierre Hansen,et al.  Variable Neighborhood Search , 2018, Handbook of Heuristics.

[12]  Chieh-Yuan Tsai,et al.  A personalized route recommendation service for theme parks using RFID information and tourist behavior , 2012, Decis. Support Syst..

[13]  Weimin Zheng,et al.  Using a heuristic algorithm to design a personalized day tour route in a time-dependent stochastic environment , 2018, Tourism Management.

[14]  Richard F. Hartl,et al.  Metaheuristics for the bi-objective orienteering problem , 2009, Swarm Intelligence.

[15]  Mimi Li,et al.  Cross-Cultural Tourist Research: A Meta-Analysis , 2014 .

[16]  Bob McKercher,et al.  Day tour itineraries: Searching for the balance between commercial needs and experiential desires , 2012 .

[17]  Anthony J. T. Lee,et al.  Tour recommendations by mining photo sharing social media , 2017, Decis. Support Syst..

[18]  Weimin Zheng,et al.  Using a heuristic approach to design personalized tour routes for heterogeneous tourist groups , 2019, Tourism Management.

[19]  Gregory Ashworth,et al.  Urban tourism research: Recent progress and current paradoxes , 2011 .

[20]  Geoffrey Wall,et al.  Point pattern analyses of accomodation in Toronto , 1985 .

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

[22]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[23]  Luiz Moutinho,et al.  Hotel location when competitors may react: A game-theoretic gravitational model , 2018, Tourism Management.

[24]  Hoong Chuin Lau,et al.  Orienteering Problem: A survey of recent variants, solution approaches and applications , 2016, Eur. J. Oper. Res..

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

[26]  Antonio Paolo Russo,et al.  Planning considerations for cultural tourism: a case study of four European cities. , 2002 .

[27]  Alan Toledo,et al.  HOPHS: A hyperheuristic that solves orienteering problem with hotel selection , 2015, 2015 Fifth International Conference on Digital Information Processing and Communications (ICDIPC).

[28]  Daniel Borrajo,et al.  Planning for tourism routes using social networks , 2017, Expert Syst. Appl..

[29]  Thorsten Teichert,et al.  Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews , 2017 .

[30]  D. Midgley,et al.  Breeding competitive strategies , 1997 .

[31]  Ching-Hsue Cheng,et al.  Recommendation system for popular tourist attractions in Taiwan using Delphi panel and repertory grid techniques. , 2015 .

[32]  Laura Vici,et al.  Pricing Visitor Preferences for Temporary Art Exhibitions , 2015 .

[33]  Parag C. Pendharkar,et al.  A general steady state distribution based stopping criteria for finite length genetic algorithms , 2007, Eur. J. Oper. Res..

[34]  Jie Zhang,et al.  Antecedents and consequences of place attachment: A comparison of Chinese and Western urban tourists in Hangzhou, China , 2016 .

[35]  J. Vittersø,et al.  Tourist experiences and attractions , 2000 .

[36]  Xiao Honggen.  Tourism and leisure in China: A tale of two cities , 1997 .

[37]  Paolo Costa,et al.  Tourism in European heritage cities , 1996 .

[38]  Farhad Samadzadegan,et al.  Time-dependent personal tour planning and scheduling in metropolises , 2011, Expert Syst. Appl..

[39]  Tony Griffin,et al.  Urban Tourism Research: Developing an Agenda , 2008 .

[40]  D. Edwards,et al.  Understanding tourists’ spatial behaviour: GPS tracking as an aid to sustainable destination management , 2013 .

[41]  Weimin Zheng,et al.  Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction , 2017 .

[42]  Dirk Cattrysse,et al.  A variable neighborhood search method for the orienteering problem with hotel selection , 2013 .

[43]  Ainhoa Urtasun,et al.  Hotel location in tourism cities: Madrid 1936–1998 , 2006 .

[44]  B. Mckercher,et al.  Modeling Tourist Movements: A Local Destination Analysis , 2006 .

[45]  Gilbert Laporte,et al.  The orienteering problem with variable profits , 2013, Networks.

[46]  Fang-Ming Hsu,et al.  Design and implementation of an intelligent recommendation system for tourist attractions: The integration of EBM model, Bayesian network and Google Maps , 2012, Expert Syst. Appl..

[47]  Mehrbakhsh Nilashi,et al.  Predicting determinants of hotel success and development using Structural Equation Modelling (SEM)-ANFIS method , 2018, Tourism Management.

[48]  Aussadavut Dumrongsiri,et al.  Optimizing customer searching experience of online hotel booking by sequencing hotel choices and selecting online reviews: A mathematical model approach , 2016 .

[49]  N. Collins-Kreiner,et al.  Evaluation of an Urban Tourism Destination , 2013 .

[50]  C. Law,et al.  Urban Tourism and its Contribution to Economic Regeneration , 1992 .

[51]  R. Vohra,et al.  The Orienteering Problem , 1987 .

[52]  Mahmoud A. Abo-Sinna,et al.  An effective genetic algorithm approach to multiobjective routing problems (MORPs) , 2005, Appl. Math. Comput..

[53]  Noam Shoval,et al.  Tracking tourists in the digital age , 2007 .

[54]  Dirk Cattrysse,et al.  A memetic algorithm for the orienteering problem with hotel selection , 2014, Eur. J. Oper. Res..

[55]  B. Mckercher,et al.  Hotel location and tourist activity in cities. , 2011 .

[56]  Kenneth Sörensen,et al.  MA mid PM: memetic algorithms with population management , 2006, Comput. Oper. Res..

[57]  M. Selby.  Consuming the city: conceptualizing and researching urban tourist knowledge , 2004 .

[58]  P. Hansen,et al.  Variable neighbourhood search: methods and applications , 2010, Ann. Oper. Res..

[59]  Natan Uriely.  The tourist experience: Conceptual Developments , 2005 .

[60]  Feifei Xu,et al.  Students' travel behaviour: a cross‐cultural comparison of UK and China , 2009 .

[61]  Nacima Labadie,et al.  Team Orienteering Problem with Decreasing Profits , 2013, Electron. Notes Discret. Math..

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

[63]  Kenneth F. Hyde,et al.  The Nature of Independent Travel , 2003 .

[64]  Dirk Van Oudheusden,et al.  The planning of cycle trips in the province of East Flanders , 2011 .

[65]  J. Q. Hu,et al.  On the tour planning problem , 2012, Ann. Oper. Res..

[66]  D. Pearce,et al.  Tourist time-budget , 1988 .

[67]  J. Crotts,et al.  The Effect of National Culture on Consumers’ Evaluation of Travel Services , 2003 .

[68]  Carlos Cotta,et al.  Memetic algorithms and memetic computing optimization: A literature review , 2012, Swarm Evol. Comput..

[69]  Dirk Cattrysse,et al.  Personalized Multi-day Trips to Touristic Regions: A Hybrid GA-VND Approach , 2014, EvoCOP.

[70]  Surya B. Yadav,et al.  The Development and Evaluation of an Improved Genetic Algorithm Based on Migration and Artificial Selection , 1994, IEEE Trans. Syst. Man Cybern. Syst..

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

[72]  Safak Aksoy,et al.  Multiple criteria decision making in hotel location: Does it relate to postpurchase consumer evaluations? , 2017 .

[73]  B. Schmitz,et al.  Networks, clusters and innovation in tourism: a UK experience , 2006 .

[74]  K. Gotham.  Destination New Orleans , 2007 .

[75]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[76]  D. Pearce,et al.  An integrative framework for urban tourism research , 2001 .

[77]  John Taplin,et al.  Car trip attraction and route choice in Australia , 1997 .

[78]  Chris Ryan,et al.  Spatial planning, mobilities and culture - Chinese and New Zealand student preferences for Californian travel. , 2007 .

[79]  N. Shoval.  The Geography of Hotels in Cities: An Empirical Validation of a Forgotten Model , 2006 .

[80]  Mimi Li,et al.  A spatial–temporal analysis of hotels in urban tourism destination , 2014, International Journal of Hospitality Management.

[81]  Stéphane Bégin.  The geography of a tourist business: Hotel distribution and urban development in Xiamen, China , 2000 .

[82]  Mahmoud A. Abo-Sinna,et al.  An effective genetic algorithm approach to multiobjective resource allocation problems (MORAPs) , 2005, Appl. Math. Comput..

[83]  Rafael Caballero,et al.  Interactive design of personalised tourism routes , 2012 .

[84]  Bob McKercher,et al.  First and Repeat Visitor Behaviour: GPS Tracking and GIS Analysis in Hong Kong , 2012 .

[85]  Stephen Shaoyi Liao,et al.  A real-time personalized route recommendation system for self-drive tourists based on vehicle to vehicle communication , 2014, Expert Syst. Appl..

[86]  Ganghua Chen,et al.  Motivations Of Repeat Visits: A Longitudinal Study in Xiamen, China , 2013 .

[87]  B. Mckercher,et al.  Movement Patterns of Tourists within a Destination , 2008 .

[88]  Mehmet Fatih Tasgetiren,et al.  Differential evolution algorithm with ensemble of parameters and mutation strategies , 2011, Appl. Soft Comput..

[89]  Theodoros Lappas,et al.  Personalized multi-period tour recommendations , 2017 .