Navigating through the complex transport system: A heuristic approach for city tourism recommendation

The fast development of machine learning and artificial intelligence has led to a great improvement of the smart tourism recommendation system, however many problems associated with the choice of transport modes in city tourism have yet to be solved. This research attempts to address this issue by p...

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Published inTourism management (1982) Vol. 81; p. 104162
Main Authors Zheng, Weimin, Liao, Zhixue, Lin, Zhibin
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2020
Subjects
City tourism
Multi-objective optimization
Nondominated sorting heuristic approach
Smart tourism
Tourism recommendation system
Transport mode choice
Smart tourism
Multi-objective optimization
Tourism recommendation system
City tourism
Transport mode choice
Nondominated sorting heuristic approach
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Abstract The fast development of machine learning and artificial intelligence has led to a great improvement of the smart tourism recommendation system, however many problems associated with the choice of transport modes in city tourism have yet to be solved. This research attempts to address this issue by proposing a model of customized day itineraries with consideration of transport mode choice. With improved particle swarm optimization and differential evolution algorithm, a nondominated sorting heuristic approach was devised. A case study was carried out in Chengdu, China to examine the performance of our approach. The results show that compared with extant methods, our approach achieves better performance. In addition, our approach can create more sensible, multifarious, and customized itineraries than previous methods. Tourism organizations and mobile map app providers could integrate our proposed model into their existing smart service systems, as part of their e-business or digital strategy for enhancing tourist experience.
AbstractList The fast development of machine learning and artificial intelligence has led to a great improvement of the smart tourism recommendation system, however many problems associated with the choice of transport modes in city tourism have yet to be solved. This research attempts to address this issue by proposing a model of customized day itineraries with consideration of transport mode choice. With improved particle swarm optimization and differential evolution algorithm, a nondominated sorting heuristic approach was devised. A case study was carried out in Chengdu, China to examine the performance of our approach. The results show that compared with extant methods, our approach achieves better performance. In addition, our approach can create more sensible, multifarious, and customized itineraries than previous methods. Tourism organizations and mobile map app providers could integrate our proposed model into their existing smart service systems, as part of their e-business or digital strategy for enhancing tourist experience.
ArticleNumber 104162
Author Liao, Zhixue
Zheng, Weimin
Lin, Zhibin
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  surname: Lin
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  organization: Durham University Business School, Mill Hill Lane, Durham, DH1 3LB, United Kingdom
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Keywords Smart tourism
Multi-objective optimization
Tourism recommendation system
City tourism
Transport mode choice
Nondominated sorting heuristic approach
Language English
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Snippet The fast development of machine learning and artificial intelligence has led to a great improvement of the smart tourism recommendation system, however many...
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StartPage 104162
SubjectTerms City tourism
Multi-objective optimization
Nondominated sorting heuristic approach
Smart tourism
Tourism recommendation system
Transport mode choice
Title Navigating through the complex transport system: A heuristic approach for city tourism recommendation
URI https://dx.doi.org/10.1016/j.tourman.2020.104162
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