Skip to main content
SpringerLink
Log in

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

  • Published:
Networks and Spatial Economics Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Abdelgawad H, Abdulhai B (2009) Emergency evacuation planning as a network design problem: a critical review. Transp Lett 1(1):41–58

    Google Scholar 

  • 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):1315–1334

    Google Scholar 

  • Bayram V, Tansel BÇ, Yaman H (2015) Compromising system and user interests in shelter location and evacuation planning. Transp Res B 72:146–163

    Google Scholar 

  • Beamon BM, Balcik B (2008) Performance measurement in humanitarian relief chains. Int J Public Sect Manage 21(1):4–25

    Google Scholar 

  • Benders JF (1962) Partitioning procedures for solving mixed variables programming problems. Numer Math 4:238–252

    Google Scholar 

  • Chen M, Chen L, Miller-Hooks E (2007) Traffic signal timing for urban evacuation. J Urban Plann Dev 133(1):30–42

    Google Scholar 

  • 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):83–94

    Google Scholar 

  • Codato G, Fischetti M (2006) Combinatorial Benders’ cuts for mixed-integer linear programming. Oper Res 54(4):756–766

    Google Scholar 

  • Cova TJ, Johnson JP (2003) A network flow model for lane-based evacuation routing. Transp Res A 37(7):579–604

    Google Scholar 

  • Daganzo C (1994) The cell transmission model. Part I: a simple dynamic representation of highway traffic. Transp Res B 28(4):269–287

    Google Scholar 

  • Daganzo C (1995) The cell transmission model, part II: network traffic. Transp Res B 29(2):79–93

    Google Scholar 

  • Dogan K, Goetschalckx M (1999) A primal decomposition method for the integrated design of multi-period production–distribution systems. IIE Trans 31(11):1027–1036

    Google Scholar 

  • El-Sbayti HH (2008) Optimal scheduling of evacuation operations with contraflow. Doctoral dissertation, University of Maryland

  • Fischetti M, Lodi A (2003) Local branching. Math Program 98(1–3):23–47

    Google Scholar 

  • Fisher ML, Jaikumar R (1981) A generalized assignment heuristic for vehicle routing. Networks 11(2):109–124

    Google Scholar 

  • Haghani A (1996) Capacitated maximum covering location models: formulations and solution procedures. J Adv Transp 30(3):101–136

    Google Scholar 

  • Hamming RW (1950) Error detecting and error correcting codes. Bell Syst Tech J 29(2):147–160

    Google Scholar 

  • He X, Peeta S (2014) Dynamic resource allocation problem for transportation network evacuation. Netw Spat Econ 14(3–4):505–530

    Google Scholar 

  • 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 59:233–347

    Google Scholar 

  • 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 137:58–68

    Google Scholar 

  • Horner M, Downs J (2007) Testing a flexible geographic information system-based network flow model for routing hurricane disaster relief goods. Transp Res Rec 2022:47–54

    Google Scholar 

  • 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):1643–1666

    Google Scholar 

  • 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):1482–1501

    Google Scholar 

  • 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 241–259

    Google Scholar 

  • Jeroslow RG (1985) The polynomial hierarchy and a simple model for competitive analysis. Math Program 32(2):146–164

    Google Scholar 

  • 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):777–807

    Google Scholar 

  • Kalafatas G, Peeta S (2009) Planning for evacuation: insights from an efficient network design model. J Infrastruct Syst 15(1):21–30

    Google Scholar 

  • Karasakal O, Karasakal EK (2004) A maximal covering location model in the presence of partial coverage. Comput Oper Res 31(9):1515–1526

    Google Scholar 

  • Karoonsoontawong A, Lin DY (2011) Time-varying lane-based capacity reversibility for traffic management. Comput Aided Civ Inf Eng 26(8):632–646

    Google Scholar 

  • 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 79:1–21

    Google Scholar 

  • Kongsomsaksakul S, Yang C, Chen A (2005) Shelter location-allocation model for flood evacuation planning. J East Asia Soc Transp Stud 6:4237–4252

    Google Scholar 

  • Kim S, Shekhar S, Min M (2008) Contraflow transportation network reconfiguration for evacuation route planning. IEEE Trans Knowl Data Eng 20(8):1115–1129

    Google Scholar 

  • Kulshrestha A, Wu D, Lou Y, Yin Y (2011) Robust shelter locations for evacuation planning with demand uncertainty. J Transp Saf Secur 3(4):272–288

    Google Scholar 

  • Li AC, Nozick L, Xu N, Davidson R (2012) Shelter location and transportation planning under hurricane conditions. Transp Res E 48(4):715–729

    Google Scholar 

  • 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):184–192

    Google Scholar 

  • Li Y, Waller ST, Ziliaskopoulos T (2003) A decomposition scheme for system optimal dynamic traffic assignment models. Netw Spat Econ 3:441–455

    Google Scholar 

  • Lo HK (2001) A cell-based traffic control formulation: strategies and benefits of dynamic timing plans. Transp Sci 35(2):148–164

    Google Scholar 

  • Lv N, Yan X, Xu K, Wu C (2010) Bi-level programming based contra flow optimization for evacuation events. Kybernetes 39(8):1227–1234

    Google Scholar 

  • Magnanti TL, Wong RT (1981) Accelerating Benders decomposition: algorithmic enhancement and model selection criteria. Oper Res 29(3):464–484

    Google Scholar 

  • 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 69:122–145

    Google Scholar 

  • Meng Q, Khoo HL (2008) Optimizing contraflow scheduling problem: model and algorithm. J Intell Transp Syst 12(3):126–138

    Google Scholar 

  • Murray-Tuite P, Wolshon B (2013) Evacuation transportation modeling: an overview of research, development, and practice. Transp Res C 27:25–45

    Google Scholar 

  • 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):547–556

    Google Scholar 

  • Ng M, Waller ST (2010) Reliable evacuation planning via demand inflation and supply deflation. Transp Res E 46(6):1086–1094

    Google Scholar 

  • Okabe A, Boots B, Sugihara K, Chiu SN (2009) Spatial tessellations: concepts and applications of Voronoi diagrams, vol. 501. John Wiley & Sons, Hoboken

    Google Scholar 

  • Patil G, Ukkusuri S (2007) System-optimal stochastic transportation network design. Transp Res Rec 2029:80–86

    Google Scholar 

  • Peeta S, Salman FS, Gunnec D, Viswanath K (2010) Pre-disaster investment decisions for strengthening a highway network. Comput Oper Res 37(10):1708–1719

    Google Scholar 

  • Peeta S, Ziliaskopoulos AK (2001) Foundations of dynamic traffic assignment: the past, the present and the future. Netw Spat Econ 1(3):233–265

    Google Scholar 

  • Rebennack S, Arulselvan A, Elefteriadou L, Pardalos PM (2010) Complexity analysis for maximum flow problems with arc reversals. J Comb Optim 19(2):200–216

    Google Scholar 

  • Rei W, Cordeau JF, Gendreau M, Soriano P (2009) Accelerating Benders decomposition by local branching. INFORMS J Comput 21(2):333–345

    Google Scholar 

  • Sheffi Y, Mahmassani H, Powell WB (1982) A transportation network evacuation model. Transp Res A 16(3):209–218

    Google Scholar 

  • 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):439–452

    Google Scholar 

  • 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):367–410

    Google Scholar 

  • Tuydes H, Ziliaskopoulos A (2004) Network re-design to optimize evacuation contraflow. In: Proc. 83rd Annual Meeting of the Transportation Research Board, paper number 04–4715

  • Tuydes H, Ziliaskopoulos A (2006) Tabu-based heuristic approach for optimization of network evacuation contraflow. Transp Res Rec 1964(1):157–168

    Google Scholar 

  • Tuydes H, Ziliaskopoulos A (2014) Modeling demand management strategies for evacuations. Ann Oper Res 217(1):491–512

    Google Scholar 

  • 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

    Google Scholar 

  • 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):295–316

    Google Scholar 

  • Xie C, Turnquist MA (2011) Land-based evacuation network optimization: an integrated Lagrangian relaxation and tabu search approach. Transp Res C 19:40–63

    Google Scholar 

  • 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 105:39–59

    Google Scholar 

  • Yang X, Ban XJ, Ma R (2017) Mixed equilibria with common constraints on transportation networks. Netw Spat Econ 17(2):547–579

    Google Scholar 

  • Yazici MA, Ozbay K (2007) Impact of probabilistic road capacity constraints on the spatial distribution of hurricane evacuation shelter capacities. Transp Res Rec 2022:55–62

    Google Scholar 

  • Yushimito WF, Jaller M, Ukkusuri S (2012) A Voronoi-based heuristic algorithm for locating distribution centers in disasters. Netw Spat Econ 12(1):21–39

    Google Scholar 

  • Zheng H, Chiu Y-C, Mirchandani P (2015) On the system optimum dynamic traffic assignment and earliest arrival flow problems. Transp Sci 49(1):13–27

    Google Scholar 

  • Zheng H, He X, Li Y, Peeta S (2017) Traffic equilibrium and charging facility location for electric vehicles. Netw Spat Econ 17(2):435–457

    Google Scholar 

Download references

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.

Author information

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

    Xiaozheng He

  2. NEXTRANS Center, Purdue University, West Lafayette, IN, 47906, USA

    Xiaozheng He, Srinivas Peeta & Yongfu Li

  3. North Central Texas Council of Governments, Arlington, TX, 76005, USA

    Hong Zheng

  4. School of Civil Engineering, Purdue University, West Lafayette, IN, 47907, USA

    Srinivas Peeta

  5. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Yongfu Li

Authors
  1. Xiaozheng He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Srinivas Peeta
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yongfu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Srinivas Peeta.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, X., Zheng, H., Peeta, S. et al. Network Design Model to Integrate Shelter Assignment with Contraflow Operations in Emergency Evacuation Planning. Netw Spat Econ 18, 1027–1050 (2018). https://doi.org/10.1007/s11067-017-9381-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11067-017-9381-y

Keywords

Search

Navigation