A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability

Takashi Hasuike; Hideki Katagiri; Hiroe Tsubaki; Hiroshi Tsuda

doi:10.1109/SMC.2015.467

A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability

Takashi Hasuike, Hideki Katagiri, Hiroe Tsubaki, Hiroshi Tsuda

研究成果

8 被引用数 (Scopus)

抄録

This paper proposes a route recommendation system for sightseeing based on a network optimization problem. Traveling and sightseeing times are randomly changed dependent on current traffic and congestion conditions, and hence, Time-Expanded Network (TEN) to contain a copy to the set of nodes in the underlying static network for each discrete time step is introduced. In addition, in order to select the next sightseeing site, conditional probabilities are introduced, which are calculated by current conditions, statistical and Web data. Our proposed model is formulated as a nonlinear and discrete optimization problem, and it is hard to solve it directly and efficiently. Therefore, an efficient algorithm is also developed based on dynamic programming and transformation of the main problem into the recursive equation.

本文言語	English
ホスト出版物のタイトル	Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	2672-2677
ページ数	6
ISBN（印刷版）	9781479986965
DOI	https://doi.org/10.1109/SMC.2015.467
出版ステータス	Published - 2016 1 12
イベント	IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong 継続期間: 2015 10 9 → 2015 10 12

Other

Other	IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
国/地域	Hong Kong
City	Kowloon Tong
Period	15/10/9 → 15/10/12

ASJC Scopus subject areas

人工知能
コンピュータネットワークおよび通信
エネルギー工学および電力技術
情報システムおよび情報管理
制御およびシステム工学

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10.1109/SMC.2015.467

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引用スタイル

Hasuike, T., Katagiri, H., Tsubaki, H., & Tsuda, H. (2016). A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability. In Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 (pp. 2672-2677). [7379599] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2015.467

Hasuike, T, Katagiri, H, Tsubaki, H & Tsuda, H 2016, A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability. in Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015., 7379599, Institute of Electrical and Electronics Engineers Inc., pp. 2672-2677, IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015, Kowloon Tong, Hong Kong, 15/10/9. https://doi.org/10.1109/SMC.2015.467

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abstract = "This paper proposes a route recommendation system for sightseeing based on a network optimization problem. Traveling and sightseeing times are randomly changed dependent on current traffic and congestion conditions, and hence, Time-Expanded Network (TEN) to contain a copy to the set of nodes in the underlying static network for each discrete time step is introduced. In addition, in order to select the next sightseeing site, conditional probabilities are introduced, which are calculated by current conditions, statistical and Web data. Our proposed model is formulated as a nonlinear and discrete optimization problem, and it is hard to solve it directly and efficiently. Therefore, an efficient algorithm is also developed based on dynamic programming and transformation of the main problem into the recursive equation.",

keywords = "conditional probabliy, Dynamic programming, mathematical programming, sightseeing route recommendation, Time-Expanded Network (TEN)",

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N2 - This paper proposes a route recommendation system for sightseeing based on a network optimization problem. Traveling and sightseeing times are randomly changed dependent on current traffic and congestion conditions, and hence, Time-Expanded Network (TEN) to contain a copy to the set of nodes in the underlying static network for each discrete time step is introduced. In addition, in order to select the next sightseeing site, conditional probabilities are introduced, which are calculated by current conditions, statistical and Web data. Our proposed model is formulated as a nonlinear and discrete optimization problem, and it is hard to solve it directly and efficiently. Therefore, an efficient algorithm is also developed based on dynamic programming and transformation of the main problem into the recursive equation.

AB - This paper proposes a route recommendation system for sightseeing based on a network optimization problem. Traveling and sightseeing times are randomly changed dependent on current traffic and congestion conditions, and hence, Time-Expanded Network (TEN) to contain a copy to the set of nodes in the underlying static network for each discrete time step is introduced. In addition, in order to select the next sightseeing site, conditional probabilities are introduced, which are calculated by current conditions, statistical and Web data. Our proposed model is formulated as a nonlinear and discrete optimization problem, and it is hard to solve it directly and efficiently. Therefore, an efficient algorithm is also developed based on dynamic programming and transformation of the main problem into the recursive equation.

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A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability

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