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: Conference contribution

7 引用（Scopus）

抜粋

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.

元の言語	English
ホスト出版物のタイトル	Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
出版者	Institute of Electrical and Electronics Engineers Inc.
ページ	2672-2677
ページ数	6
ISBN（印刷物）	9781479986965
DOI	https://doi.org/10.1109/SMC.2015.467
出版物ステータス	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	Hong Kong
市	Kowloon Tong
期間	15/10/9 → 15/10/12

フィンガープリント

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Energy Engineering and Power Technology
Information Systems and Management
Control and Systems Engineering

これを引用

Hasuike, T., Katagiri, H., Tsubaki, H., & Tsuda, H. (2016). A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability. ： 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

A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability. / Hasuike, Takashi; Katagiri, Hideki; Tsubaki, Hiroe; Tsuda, Hiroshi.

Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 2672-2677 7379599.

研究成果: Conference contribution

Hasuike, T, Katagiri, H, Tsubaki, H & Tsuda, H 2016, A Route Recommendation System for Sightseeing with Network Optimization and Conditional Probability. ： 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.",

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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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文献にアクセス

10.1109/SMC.2015.467