On the tour planning problem

Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sit...

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Vydané v:	Annals of operations research Ročník 192; číslo 1; s. 67 - 86
Hlavní autori:	Zhu, Chenbo, Hu, J. Q., Wang, Fengchun, Xu, Yifan, Cao, Rongzeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Boston Springer US 01.01.2012 Springer Science + Business Media Springer Springer Nature B.V
Predmet:	Advisory services Algorithms Approximation Approximation theory Business and Management Catering Combinatorics Computation Customers Electronic commerce Heuristic Hotels & motels Laboratories Linear programming Mathematical analysis Mathematical models Methods Mixed integer Operations research Operations Research/Decision Theory Orienteering Planning Recommender systems Studies Technology application Theory of Computation Tourism Tours Travel Travel agencies Travel industry Websites China Local search Team orienteering problem Mixed integer linear programming Tour planning problem Heuristic
ISSN:	0254-5330, 1572-9338
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Abstract	Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20–30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods.
AbstractList	Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20-30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods. Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20-30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods. Keywords Tour planning problem * Team orienteering problem * Mixed integer linear programming * Heuristic * Local search Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20-30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods. [PUBLICATION ABSTRACT] Increasingly, tourists are planning trips by themselves using the vast amount of information available on the Web. However, they still expect and want trip plan advisory services. In this paper, we study the tour planning problem in which our goal is to design a tour trip with the most desirable sites, subject to various budget and time constraints. We first establish a framework for this problem, and then formulate it as a mixed integer linear programming problem. However, except when the size of the problem is small, say, with less than 20–30 sites, it is computationally infeasible to solve the mixed-integer linear programming problem. Therefore, we propose a heuristic method based on local search ideas. The method is efficient and provides good approximation solutions. Numerical results are provided to validate the method. We also apply our method to the team orienteering problem, a special case of the tour planning problem which has been considered in the literature, and compare our method with other existing methods. Our numerical results show that our method produces very good approximation solutions with relatively small computational efforts comparing with other existing methods.
Audience	Academic
Author	Cao, Rongzeng Zhu, Chenbo Hu, J. Q. Xu, Yifan Wang, Fengchun
Author_xml	– sequence: 1 givenname: Chenbo surname: Zhu fullname: Zhu, Chenbo organization: Department of Management Science, School of Management, Fudan University – sequence: 2 givenname: J. Q. surname: Hu fullname: Hu, J. Q. email: hujq@fudan.edu.cn organization: Department of Management Science, School of Management, Fudan University – sequence: 3 givenname: Fengchun surname: Wang fullname: Wang, Fengchun organization: IBM China Research Laboratory – sequence: 4 givenname: Yifan surname: Xu fullname: Xu, Yifan organization: Department of Management Science, School of Management, Fudan University – sequence: 5 givenname: Rongzeng surname: Cao fullname: Cao, Rongzeng organization: IBM China Research Laboratory
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Cites_doi	10.1287/ijoc.8.2.158 10.1016/j.tourman.2008.01.005 10.1016/0377-2217(94)00289-4 10.1016/j.cie.2007.10.001 10.1016/j.ejor.2008.02.037 10.1007/s10732-006-9004-0 10.1145/336992.337035 10.1057/jors.1995.204 10.1002/j.1538-7305.1965.tb04146.x
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