Journal of Environmental
1684-8799 / Print ISSN 1726-2135
© 2008 ISEIS.
All rights reserved.
TISEM: A Two-Stage Interval-Stochastic Evacuation Management Model
G. C. Li1, G. H. Huang1*, C. Z. Wu2, Y. P. Li3, Y. M. Chen1 and Q. Tan1
- Faculty of Engineering, University of Regina, Regina, Saskathewan S4S 0A2, Canada
- Intelligent Transportation System Research Center, Wuhan University of Technology, Wuhan 430070, P. R. China
- College of Urban and Environmental Sciences, Peking University, Beijing 100871, P. R. China
*Corresponding author. Tel: +1 306 5854095 Fax: +1 306 5854855 Email: email@example.com
Traffic allocation planning is commonly required for mass evacuation management. It primarily relies on efficient coordination and appropriate utilization of roadway capacity and available traffic resources. However, traffic and evacuee information are usually difficult to be obtained and consequently of various uncertainties in data. Especially, stochastic information may often exist in evacuation management systems. In this study, a two-stage interval stochastic evacuation management (TISEM) model was developed for supporting the evacuation planning under uncertainty, by which stochastic and interval evacuation information could be well reflected and communicated in the system. In addition, by adopting the proposed model, a case study abstracted from the City of Wuhan was introduced and solved through an interactive method. Results indicated that useful solutions for planning evacuation routes could be generated based on results of the model. As well, through the model, complex relationships between evacuation time, environmental influences and economic factors could be systematically analyzed. It demonstrated that the proposed TISP model is practical and applicable in real world, and is helpful for authorities to make decisions allocating vehicles before evacuation starts.
Keywords: allocation planning, management, optimization, stadium evacuation, transportation, uncertainty
Full Text (PDF) | Export citation to: EndNote RefMan
Cite this paper as: G. C. Li, G. H. Huang, C. Z. Wu, Y. P. Li, Y. M. Chen and Q. Tan, 2008. TISEM: A Two-Stage Interval-Stochastic Evacuation Management Model. Journal of Environmental Informatics, 12(1), 64-74. http://dx.doi.org/10.3808/jei.200800125
- Bakuli, D.L. and Smith, J.M. (1996). Resource allocation in state-dependent emergency evacuation networks, European Journal of Operational Research, 89, 543-555. http://dx.doi.org/10.1016/0377-2217(94)00230-4
- Cova, T.J. and Johnson, J.P. (2003). A network flow model for lane-based evacuation routing, Transp. Res. A, 37, 579-604. http://dx.doi.org/10.1016/S0965-8564(03)00007-7
- Decker, S.H., Varano, S.P. and Greene, J.R. (2007). Routine crime in exceptional times: The impact of the 2002 Winter Olympics on citizen demand for police services, J. Crim. Just., 35(1), 89-101. http://dx.doi.org/10.1016/j.jcrimjus.2006.11.018
- Ettema, D. and Timmermans, H. (2006). Costs of travel time uncertainty and benefits of travel time information: Conceptual model and numerical examples, Transp. Res. C, 14, 335-350. http://dx.doi.org/10.1016/j.trc.2006.09.001
- Frantzeskakis, J.M. and Frantzeskakis, M.J. (2006). Athens 2004 Olympic Games: Transportation Planning, Simulation and Traffic Management, ITE Journal, 76(10), 26-33.
- Graata, E., Middena, C. (1999). Complex evacuation: effects of motivation level and slope of stairs on emergency egress time in a sports stadium, Safety Science, 31, 127-141. http://dx.doi.org/10.1016/S0925-7535(98)00061-7
- Grivas, G. and Chaloulakou, A. (2006). Artificial neural network models for prediction of PM10 hourly concentrations, in the Greater Area of Athens, Greece, Atmospheric Environment, 40, 1216-1229. http://dx.doi.org/10.1016/j.atmosenv.2005.10.036
- Hobeika, A.G. and Kim, C. (1998). Comparison of Traffic Assignments in Evacuation Modeling, IEEE Transactions on Engineering Management, 45(2), 192-198.
- Huang, G. and Moore, R.D. (1993). Grey Linear Programming, its Solving Approach, and its Application, International Journal of Systems Science, 24, 159-172.
- Huang, G., Baetz, B.W. and Patry, G.G. (1994). Capacity Planning for Municipal Solid Waste Management Systems under Uncertainty: A Grey Fuzzy Dynamic Programming (GFDP) Approach, J. Urban Plann. Dev., 120, 132-156.
- Huang, G.H. (1996). IPWM: An Interval Parameter Water Quality Management Model, Eng. Optimiz., 26, 79-103.
- Huang, G.H. and Louck, D.P. (2000). An Inexact Two-Stage Stochastic Programming Model for Water Resources Management under Uncertainty, Civ. Eng. Environ. Syst., 17, 95-118. http://dx.doi.org/10.1007/s11269-007-9206-8
- Li, Y.P. and Huang, G.H. (2006). An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina, J. Environ. Manage., 81, 188-209. http://dx.doi.org/10.1016/j.jenvman.2005.10.007
- Lv, W., Wang, Y., Querol, X., Zhuang, X., Alastuey, A., López, A. and Viana, M. (2006). Geochemical and statistical analysis of trace metals in atmospheric particulates in Wuhan, central China, Environ. Geol., 51, 121-132. http://dx.doi.org/10.1007/s00254-006-0310-5
- Maqsood, I. and Huang, G.H. (2003). A two-stage interval-stochastic programming model for waste management under uncertainty, Journal of the Air and Waste Management Association, 53(5), 540-552.
- Maqsood, I., Huang, G.H. and Zeng, G.M. (2004). An inexact two-stage mixed integer linear programming model for waste management under uncertainty, Civ. Eng. Environ. Syst., 21(3), 187-206.
- Querol, X., Zhuang, X., Alastuey, A., Viana, M., Lv, W., Wang, Y., LĘ«pez, A., Zhu, Z., Wei, H. and Xu, S. (2006). Speciation and sources of atmospheric aerosols in a highly industrialized emerging mega-city in Central China, J. Environ. Monit., 8, 1049-1059.
- Sattayhatewa, P. and Ran, B. (2000). Developing a dynamic traffic management model for nuclear power plant evacuation, Transportation Research Board Annual Meeting, 1-24.
- Southworth, F. (1991). Regional evacuation modeling: a state-of-the-art review, Oak Ridge National Labs, ORNL/TM-11740.
- Suleyman, T. (1995). An integrated emergency management decision support system for hurricane emergencies, Safety Science, 20, 39-48. http://dx.doi.org/10.1016/0925-7535(94)00065-B
- Tan, Q., Huang, G.H. and Wu, C.Z. (2008). Development of an Inexact Fuzzy Robust Programming Model for Integrated Evacuation Management under Uncertainty, in press.
- Urbanik, T. (2000). Evacuation time estimates for nuclear power plants, J. Hazard. Mater., 75, 165-180. http://dx.doi.org/10.1016/S0304-3894(00)00178-3
- Waller, S.T., Schofer, J.L. and Ziliaskopoulos, A.K. (2001). Evaluation with traffic assignment under demand uncertainty, J. Trans. Res. Board, 1771, 69-75. http://dx.doi.org/10.3141/1771-09
- Waller, S.T. and Ziliaskopoulos, A.K. (2006). A chance-constrained based stochastic dynamic traffic assignment model: Analysis, formulation and solution algorithms, Transp. Res. C, 14, 418- 427. http://dx.doi.org/10.1016/j.trc.2006.11.002
- Wu, C.Z., Huang, G.H., Yan, X.P., Cai, Y.P. and Li, Y.P. (2008). An inexact optimization model for evacuation planning. Kybernetes, In press.
- Yi, W. and Zdamar, L.O. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities, European Journal of Operational Research, 179, 1177-1193. http://dx.doi.org/10.1016/j.ejor.2005.03.077