Browse > Article

Analysis of Tour Information Services using Agent-based Simulation  

Kim, Hyeon-Myeong (candidate, UC. Irvine)
O, Jun-Seok (Western Michigan University)
Publication Information
Journal of Korean Society of Transportation / v.24, no.6, 2006 , pp. 103-117 More about this Journal
Abstract
This study develops an agent-based simulation model to evaluate tourist information systems under ubiquitous environment. In this study, individual tourist's activity chaining behavior is formulated as a utility maximization problem. The underlying assumption of the model is that tourists increase their activities within their time and budget constraints to maximize their utilities. The model seeks individual's optimal tour schedule by solving Prize-Collecting Multiple-Day Traveling Salesman Problem(PC MD TSP). The simulation-based evaluation framework allows investigating individual utility gains by their information type and the total expenditure at each tour attractions. The real-time tour activity scheduling system enables tourists to optimize their tour activities by minimizing their time loss and maximizing their opportunity to use high utility facilities.
Keywords
Tour Scheduling model; Ubiquitous environment; Prize-Collecting Multiple-Day Traveling Salesman Problem; Tour Information;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Recker W. W., M. G. McNally, G. S. Root(1986b), A model of complex travel behavior : Part II-Operational model, Transportation Research part a. vol. 20A. pp.319-330
2 MATSIM, Multi Agent Traffic SIMulation, The SIM group, http://www.matsim.org, Accessed July 2006
3 TRANSIM, TRansportation ANalysis and SIMulation System, Los Alamos National Laboratory, Los Alamos, NM., http://transim.tsasa. lanl.gov, Accessed July 2006
4 http://lcm.csa.iisc.ernet.in/dsa/dsa.html
5 http://en.wikipedia.org/wiki/Traveling_salesman_problem
6 배영석.김대웅(1990), 개별 로짓 모형을 이용한 비취업자의 1일 통행행태에 관한 연구, 대한교통학회지, 제8권 제1호, 대한교통학회, pp.89-102
7 신동호(1993), 교통수단 선택행태 분석을 위한 태도모형의 적용 및 평가, 대한교통학회지, 제11권 제2호, 대한교통학회, pp.5-26
8 이종규(2001), 서울시 권역별 관광개발계획 연구, 서울시정개발연구원
9 전효재(2003), 국제관광 수요예측, 한국문화관광 정책연구원
10 Arentze, T. A., H. J. P. Timmermans(2004) A learning-based transportation oriented simulation model, Transportation Research part b. vol. 38B. pp.613-633
11 Balmer, M., K. Axhausen, K. Nagel(2006), An agent-based demand-modeling framework for large scale micro-simulations, Transportation Research Board Meeting at Washington D.C
12 Bhat, C.R., J. Y. Guo, S. Srinivasan, and A. Sivakumar(2004), Comprehensive econometric microsimulator for daily activity-travel patterns, Transportation Research Record: Journal of the Transportation Research Board 1894, pp.57-66   DOI
13 Bowman, J.L. and Ben-Akiva, M.E.(2003), Activity based disaggregate travel demand model system with activity schedules, Transportation Research 35A, pp.1-28
14 Nakayama, S. and R. Kitamura(2000), A Route Choice Model with Inductive Learning, Transportation Research Record: Journal of Transportation Research Board, No. 1725, pp.63-70
15 Held, M. and R. M. Karp(1970), The travelling salesman problem and minimum spanning trees. Oper. Res. 18, pp.1138-1162   DOI   ScienceOn
16 Kim H., J. Oh, R. Jayakrishinan(2006), Activity Chaining Model Incorporating Time Use Problem and Its Application to Network Demand Analysis, accepted for Transportation Research Record
17 Kitamura R.(1984), Incorporating trip chaining into analysis of destination choice, Transportation Research part b. vol. 18B. pp.67-81
18 배영석(1996), 개별행태모형을 이용한 통근인구의 교통행동분석에 관한 연구, 대한교통학회지, 제14 권 제4호, 대한교통학회, pp.31-48
19 Horowitz, J.(1980), A utility maximizing model of the demand for multi-destination non-work travel, Transportation Research part b. vol. 14B. pp.369-386
20 조광익(1999), 관광수요 예측 및 경제적 파급효과 분석, 한국관광연구원
21 http://www.densis.fee.unicamp.br/~moscato/TSPBIB_home.html
22 Bienstock, D., M. X. Goemans, D. Simchi-Levi, and D. Williamson(1993), A note on the prize collecting traveling salesman problem. Mathematical Programming, 59:413-420   DOI
23 Recker W. W., M. G. McNally, G. S. Root(1986a), A model of complex travel behavior : Part I-Theoretical development, Transportation Research part a. vol. 20A. pp.307-318
24 윤대식(1997), 통근통행자의 통행패턴 선택행태의 분석, 대한교통학회지, 제15권 제4호, 대한교통학 회, pp.35-5
25 Kitamura R., E. I. Pas, C. V. Lula, T. K. Lawton, Benson, P. E.(1996), The sequenced activity mobility simulator(SAMS) : an integrated approach to modeling transportation, land use and air quality, Transportation, 23, pp.267-291
26 Balas, E.(1989), The Prize Collecting Traveling Salesman Problem, Networks 19, pp.621-636   DOI
27 Kim H., J. Oh, R. Jayakrishinan(2005), Relaxing the user equilibrium assumptions and its effects on traffic pattern and network behavior, Transportation Research Board Meeting at Washington D.C
28 Kitamura R.(1988), An evaluation of activity based travel analysis, Transportation, 15, 9-34
29 Pendyala, R. M., R. Kitamura and D. V. G. P. Reddy(1998), Application of an activitybased travel demand model incorporating a rule-based algorithm, Environment and Planning B, 25, pp.753-772   DOI   ScienceOn
30 Recker W. W.(1995), The household activity pattern problem: general formulation and solution, Transportation Research part b. vol. 29B. pp.61-77
31 Blum, S. Chawla, D. Karger, T. Lane, A. Meyerson, and M. Minkoff(2003), Approximation algorithms for orienteering and discounted-reward tsp. In Proceedings of the 44th Foundations of Computer Science
32 Recker W. W., T. F. Golob(1979), A noncompensatory model of Transportation behavior based on sequential consideration of attributes, Transportation Research part b. vol. 13B. pp.269-280