Advertisement

Networks and Spatial Economics

, Volume 18, Issue 4, pp 1027–1050 | Cite as

Network Design Model to Integrate Shelter Assignment with Contraflow Operations in Emergency Evacuation Planning

  • Xiaozheng He
  • Hong Zheng
  • Srinivas PeetaEmail author
  • Yongfu Li
Article

Abstract

In traditional emergency evacuation planning, shelter assignment and contraflow operations are determined sequentially. In this paper, we show that these two types of network design should be considered simultaneously to achieve a better evacuation performance. A mixed integer linear program is proposed, in which an earliest arrival flow model is employed to describe the underlying system optimum evacuation traffic flow pattern. The embedded earliest arrival flow model, built upon a node-link network representation, helps to maintain a small problem size. To address the computational difficulty, an accelerated Benders decomposition algorithm is developed to leverage the separable structure of the proposed model. Numerical experiments are used to investigate the effectiveness of the proposed model and solution algorithm. The results illustrate that the integrated consideration of shelter assignment and contraflow operations in evacuation planning facilitates the effective usage of the evacuation network capacity to further reduce the total system travel time in emergency evacuation.

Keywords

Evacuation planning Integrated network design Shelter location allocation Contraflow Mixed integer linear program Benders decomposition Local branching 

Notes

Acknowledgments

This work is based on funding provided by the U.S. Department of Transportation through the NEXTRANS Center, the USDOT Region 5 University Transportation Center, and partly supported by the National Natural Science Foundation of China (Grant No.61304197), the Scientific and Technological Talents Project of Chongqing (Grant No. cstc2014kjrc-qnrc30002), and National Key Research and Development Program under Grant No. 2016YFB0100906. The authors are solely responsible for the contents of this paper.

References

  1. Abdelgawad H, Abdulhai B (2009) Emergency evacuation planning as a network design problem: a critical review. Transp Lett 1(1):41–58CrossRefGoogle Scholar
  2. Afandizadeh S, Jahangiri A, Kalantari N (2013) Identifying the optimal configuration of one-way and two-way streets for contraflow operation during an emergency evacuation. Nat Hazards 69(3):1315–1334CrossRefGoogle Scholar
  3. Bayram V, Tansel BÇ, Yaman H (2015) Compromising system and user interests in shelter location and evacuation planning. Transp Res B 72:146–163CrossRefGoogle Scholar
  4. Beamon BM, Balcik B (2008) Performance measurement in humanitarian relief chains. Int J Public Sect Manage 21(1):4–25CrossRefGoogle Scholar
  5. Benders JF (1962) Partitioning procedures for solving mixed variables programming problems. Numer Math 4:238–252CrossRefGoogle Scholar
  6. Chen M, Chen L, Miller-Hooks E (2007) Traffic signal timing for urban evacuation. J Urban Plann Dev 133(1):30–42CrossRefGoogle Scholar
  7. Chiu YC, Zheng H, Villalobos J, Gautam B (2007) Modeling no-notice mass evacuation using a dynamic traffic flow optimization model. IIE Trans 39(1):83–94CrossRefGoogle Scholar
  8. Codato G, Fischetti M (2006) Combinatorial Benders’ cuts for mixed-integer linear programming. Oper Res 54(4):756–766CrossRefGoogle Scholar
  9. Cova TJ, Johnson JP (2003) A network flow model for lane-based evacuation routing. Transp Res A 37(7):579–604Google Scholar
  10. Daganzo C (1994) The cell transmission model. Part I: a simple dynamic representation of highway traffic. Transp Res B 28(4):269–287CrossRefGoogle Scholar
  11. Daganzo C (1995) The cell transmission model, part II: network traffic. Transp Res B 29(2):79–93CrossRefGoogle Scholar
  12. Dogan K, Goetschalckx M (1999) A primal decomposition method for the integrated design of multi-period production–distribution systems. IIE Trans 31(11):1027–1036Google Scholar
  13. El-Sbayti HH (2008) Optimal scheduling of evacuation operations with contraflow. Doctoral dissertation, University of MarylandGoogle Scholar
  14. Fischetti M, Lodi A (2003) Local branching. Math Program 98(1–3):23–47CrossRefGoogle Scholar
  15. Fisher ML, Jaikumar R (1981) A generalized assignment heuristic for vehicle routing. Networks 11(2):109–124CrossRefGoogle Scholar
  16. Haghani A (1996) Capacitated maximum covering location models: formulations and solution procedures. J Adv Transp 30(3):101–136CrossRefGoogle Scholar
  17. Hamming RW (1950) Error detecting and error correcting codes. Bell Syst Tech J 29(2):147–160CrossRefGoogle Scholar
  18. He X, Peeta S (2014) Dynamic resource allocation problem for transportation network evacuation. Netw Spat Econ 14(3–4):505–530CrossRefGoogle Scholar
  19. He X, Zheng H, Peeta S (2015) Model and a solution algorithm for the dynamic resource allocation problem for large-scale transportation network evacuation. Transp Res C 59:233–347CrossRefGoogle Scholar
  20. Hong L, Ouyang M, Peeta S, He X, Yan Y (2015) Vulnerability assessment and mitigation for the Chinese railway system under floods. Reliab Eng Syst Saf 137:58–68CrossRefGoogle Scholar
  21. Horner M, Downs J (2007) Testing a flexible geographic information system-based network flow model for routing hurricane disaster relief goods. Transp Res Rec 2022:47–54CrossRefGoogle Scholar
  22. Hu F, Xu W, Li X (2012) A modified particle swarm optimization algorithm for optimal allocation of earthquake emergency shelters. Int J Geogr Inf Sci 26(9):1643–1666CrossRefGoogle Scholar
  23. Hu F, Yang S, Xu W (2014) A non-dominated sorting genetic algorithm for the location and districting planning of earthquake shelters. Int J Geogr Inf Sci 28(7):1482–1501CrossRefGoogle Scholar
  24. Jabari SE, He X, Liu HX (2012) Heuristic solution techniques for no-notice emergency evacuation traffic management. In: Levinson DM, Liu HX, Bell M (eds) Network Reliability in Practice. Springer, New York, pp 241–259CrossRefGoogle Scholar
  25. Jeroslow RG (1985) The polynomial hierarchy and a simple model for competitive analysis. Math Program 32(2):146–164CrossRefGoogle Scholar
  26. Ji X, Ban XJ, Li M, Zhang J, Ran B (2017) Non-expected route choice model under risk on stochastic traffic networks. Netw Spat Econ 17(3):777–807CrossRefGoogle Scholar
  27. Kalafatas G, Peeta S (2009) Planning for evacuation: insights from an efficient network design model. J Infrastruct Syst 15(1):21–30CrossRefGoogle Scholar
  28. Karasakal O, Karasakal EK (2004) A maximal covering location model in the presence of partial coverage. Comput Oper Res 31(9):1515–1526CrossRefGoogle Scholar
  29. Karoonsoontawong A, Lin DY (2011) Time-varying lane-based capacity reversibility for traffic management. Comput Aided Civ Inf Eng 26(8):632–646CrossRefGoogle Scholar
  30. Khatami M, Mahootchi M, Farahani RZ (2015) Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties. Transp Res E 79:1–21CrossRefGoogle Scholar
  31. Kongsomsaksakul S, Yang C, Chen A (2005) Shelter location-allocation model for flood evacuation planning. J East Asia Soc Transp Stud 6:4237–4252Google Scholar
  32. Kim S, Shekhar S, Min M (2008) Contraflow transportation network reconfiguration for evacuation route planning. IEEE Trans Knowl Data Eng 20(8):1115–1129CrossRefGoogle Scholar
  33. Kulshrestha A, Wu D, Lou Y, Yin Y (2011) Robust shelter locations for evacuation planning with demand uncertainty. J Transp Saf Secur 3(4):272–288CrossRefGoogle Scholar
  34. Li AC, Nozick L, Xu N, Davidson R (2012) Shelter location and transportation planning under hurricane conditions. Transp Res E 48(4):715–729CrossRefGoogle Scholar
  35. Li AC, Xu N, Nozick L, Davidson R (2011) Bilevel optimization for integrated shelter location analysis and transportation planning for hurricane events. J Infrastruct Syst 17(4):184–192CrossRefGoogle Scholar
  36. Li Y, Waller ST, Ziliaskopoulos T (2003) A decomposition scheme for system optimal dynamic traffic assignment models. Netw Spat Econ 3:441–455CrossRefGoogle Scholar
  37. Lo HK (2001) A cell-based traffic control formulation: strategies and benefits of dynamic timing plans. Transp Sci 35(2):148–164CrossRefGoogle Scholar
  38. Lv N, Yan X, Xu K, Wu C (2010) Bi-level programming based contra flow optimization for evacuation events. Kybernetes 39(8):1227–1234CrossRefGoogle Scholar
  39. Magnanti TL, Wong RT (1981) Accelerating Benders decomposition: algorithmic enhancement and model selection criteria. Oper Res 29(3):464–484CrossRefGoogle Scholar
  40. Marufuzzaman M, Eksioglu SD, Li X, Wang J (2014) Analyzing the impact of intermodal-related risk to the design and management of biofuel supply chain. Transp Res E 69:122–145CrossRefGoogle Scholar
  41. Meng Q, Khoo HL (2008) Optimizing contraflow scheduling problem: model and algorithm. J Intell Transp Syst 12(3):126–138CrossRefGoogle Scholar
  42. Murray-Tuite P, Wolshon B (2013) Evacuation transportation modeling: an overview of research, development, and practice. Transp Res C 27:25–45CrossRefGoogle Scholar
  43. Ng M, Park J, Waller ST (2010) A hybrid bilevel model for the optimal shelter assignment in emergency evacuations. Comput Aided Civ Inf Eng 25(8):547–556CrossRefGoogle Scholar
  44. Ng M, Waller ST (2010) Reliable evacuation planning via demand inflation and supply deflation. Transp Res E 46(6):1086–1094CrossRefGoogle Scholar
  45. Okabe A, Boots B, Sugihara K, Chiu SN (2009) Spatial tessellations: concepts and applications of Voronoi diagrams, vol. 501. John Wiley & Sons, HobokenGoogle Scholar
  46. Patil G, Ukkusuri S (2007) System-optimal stochastic transportation network design. Transp Res Rec 2029:80–86CrossRefGoogle Scholar
  47. Peeta S, Salman FS, Gunnec D, Viswanath K (2010) Pre-disaster investment decisions for strengthening a highway network. Comput Oper Res 37(10):1708–1719CrossRefGoogle Scholar
  48. Peeta S, Ziliaskopoulos AK (2001) Foundations of dynamic traffic assignment: the past, the present and the future. Netw Spat Econ 1(3):233–265CrossRefGoogle Scholar
  49. Rebennack S, Arulselvan A, Elefteriadou L, Pardalos PM (2010) Complexity analysis for maximum flow problems with arc reversals. J Comb Optim 19(2):200–216CrossRefGoogle Scholar
  50. Rei W, Cordeau JF, Gendreau M, Soriano P (2009) Accelerating Benders decomposition by local branching. INFORMS J Comput 21(2):333–345CrossRefGoogle Scholar
  51. Sheffi Y, Mahmassani H, Powell WB (1982) A transportation network evacuation model. Transp Res A 16(3):209–218CrossRefGoogle Scholar
  52. Sherali HD, Carter TB, Hobeika AG (1991) A location-allocation model and algorithm for evacuation planning under hurricane/flood conditions. Transp Res B 25(6):439–452CrossRefGoogle Scholar
  53. Sherali HD, Desai J, Glickman TS (2004) Allocating emergency response resources to minimize risk with equity considerations. Am J Math Manag Sci 24(3–4):367–410Google Scholar
  54. Tuydes H, Ziliaskopoulos A (2004) Network re-design to optimize evacuation contraflow. In: Proc. 83rd Annual Meeting of the Transportation Research Board, paper number 04–4715Google Scholar
  55. Tuydes H, Ziliaskopoulos A (2006) Tabu-based heuristic approach for optimization of network evacuation contraflow. Transp Res Rec 1964(1):157–168CrossRefGoogle Scholar
  56. Tuydes H, Ziliaskopoulos A (2014) Modeling demand management strategies for evacuations. Ann Oper Res 217(1):491–512CrossRefGoogle Scholar
  57. Wang J, Du M, Lu L, He X (2017) Maximizing network throughput under stochastic user equilibrium with elastic demand. Netw Spat Econ.  https://doi.org/10.1007/s11067-017-9372-z
  58. Xie C, Lin DY, Waller ST (2010) A dynamic evacuation network optimization problem with lane reversal and crossing elimination strategies. Transp Res E 46(3):295–316CrossRefGoogle Scholar
  59. Xie C, Turnquist MA (2011) Land-based evacuation network optimization: an integrated Lagrangian relaxation and tabu search approach. Transp Res C 19:40–63CrossRefGoogle Scholar
  60. Yan Y, Hong L, He X, Ouyang M, Peeta S, Chen X (2017) Pre-disaster investment decisions for strengthening the Chinese railway system under earthquakes. Transp Res E 105:39–59Google Scholar
  61. Yang X, Ban XJ, Ma R (2017) Mixed equilibria with common constraints on transportation networks. Netw Spat Econ 17(2):547–579CrossRefGoogle Scholar
  62. Yazici MA, Ozbay K (2007) Impact of probabilistic road capacity constraints on the spatial distribution of hurricane evacuation shelter capacities. Transp Res Rec 2022:55–62CrossRefGoogle Scholar
  63. Yushimito WF, Jaller M, Ukkusuri S (2012) A Voronoi-based heuristic algorithm for locating distribution centers in disasters. Netw Spat Econ 12(1):21–39CrossRefGoogle Scholar
  64. Zheng H, Chiu Y-C, Mirchandani P (2015) On the system optimum dynamic traffic assignment and earliest arrival flow problems. Transp Sci 49(1):13–27CrossRefGoogle Scholar
  65. Zheng H, He X, Li Y, Peeta S (2017) Traffic equilibrium and charging facility location for electric vehicles. Netw Spat Econ 17(2):435–457CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringRensselaer Polytechnic InstituteTroyUSA
  2. 2.NEXTRANS CenterPurdue UniversityWest LafayetteUSA
  3. 3.North Central Texas Council of GovernmentsArlingtonUSA
  4. 4.School of Civil EngineeringPurdue UniversityWest LafayetteUSA
  5. 5.College of AutomationChongqing University of Posts and TelecommunicationsChongqingChina

Personalised recommendations