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Network Capacity Reliability Analysis Considering Traffic Regulation after a Major Disaster

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  • Agachai Sumalee

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  • Fumitaka Kurauchi

Abstract

The focuses of this paper are optimal traffic regulation after a major disaster and evaluation of capacity reliability of a network. The paper firstly discusses the context of traffic regulation and its importance after a major disaster. Then, this problem is formulated as an optimisation program in which the traffic regulator attempts to regulate the amount of traffic movements or access to some areas so as to maximise the traffic volumes in the network while (a) link flows must be less than link capacities and (b) re-routing effect due to changes of traffic condition in the network is allowed. The re-routing behaviour is assumed to follow Probit Stochastic User's Equilibrium (SUE). The paper explains an optimisation algorithm based on an implicit programming approach for solving this problem with the SUE condition. With this optimisation problem, the randomness of the link capacities (to represent random effects of the disaster) is introduced and the paper describes an approach to approximate the capacity reliability of the network using Monte-Carlo simulation. The paper then adopts this approach to evaluate the performances of different traffic regulation policies with a small network and a test network of Kobe city in Japan. Copyright Springer Science + Business Media, LLC 2006

Suggested Citation

  • Agachai Sumalee & Fumitaka Kurauchi, 2006. "Network Capacity Reliability Analysis Considering Traffic Regulation after a Major Disaster," Networks and Spatial Economics, Springer, vol. 6(3), pages 205-219, September.
  • Handle: RePEc:kap:netspa:v:6:y:2006:i:3:p:205-219
    DOI: 10.1007/s11067-006-9280-0
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    References listed on IDEAS

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    1. Du, Zhen-Ping & Nicholson, Alan, 1997. "Degradable transportation systems: Sensitivity and reliability analysis," Transportation Research Part B: Methodological, Elsevier, vol. 31(3), pages 225-237, June.
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    1. repec:eee:transe:v:103:y:2017:i:c:p:87-108 is not listed on IDEAS
    2. Turner, Jonathan P. & Qiao, Jianhong & Lawley, Mark & Richard, Jean-Philippe & Abraham, Dulcy M., 2012. "Mitigating shortage and distribution costs in damaged water networks," Socio-Economic Planning Sciences, Elsevier, vol. 46(4), pages 315-326.
    3. Zhu, Shanjiang & Levinson, David & Liu, Henry X. & Harder, Kathleen, 2010. "The traffic and behavioral effects of the I-35W Mississippi River bridge collapse," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 771-784, December.
    4. Ng, ManWo & Waller, S. Travis, 2010. "A computationally efficient methodology to characterize travel time reliability using the fast Fourier transform," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1202-1219, December.
    5. Wang, Xinchang, 2016. "Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 334-357.
    6. Wang, Xinchang, 2016. "Optimal allocation of limited and random network resources to discrete stochastic demands for standardized cargo transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 310-331.
    7. Federico Rupi & Silvia Bernardi & Guido Rossi & Antonio Danesi, 2015. "The Evaluation of Road Network Vulnerability in Mountainous Areas: A Case Study," Networks and Spatial Economics, Springer, vol. 15(2), pages 397-411, June.
    8. Bo Zhang & Hongwei Ding & Hongbo Li & Wei Wang & Tao Yao, 2014. "A Sampling-Based Stochastic Winner Determination Model for Truckload Service Procurement," Networks and Spatial Economics, Springer, vol. 14(2), pages 159-181, June.
    9. Edrissi, Ali & Nourinejad, Mehdi & Roorda, Matthew J., 2015. "Transportation network reliability in emergency response," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 56-73.

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