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Natural Computing

, Volume 18, Issue 4, pp 815–823 | Cite as

On an integrated approach to resilient transportation systems in emergency situations

  • J. W. WangEmail author
  • H. F. Wang
  • Y. M. Zhou
  • Y. Wang
  • W. J. Zhang
Article

Abstract

In this paper we present an integrated approach to the evacuation problem under an emergency situation for transportation systems. The approach is based on a view that a service system has two subsystems: infrastructure and substance. The approach attempts to integrate infrastructure design and substance flow planning to improve the evacuation performance. Without loss of generality, we restrict infrastructure design to reconstruction of a damaged road with two attributes of the road: capacity and travel time, we restrict substance flow planning to the contraflow method, and we consider the evacuation problem with single source and single destination. Further, we apply the discrete variable Particle Swarm Optimization and RelaxIV to solve the problem model. The overall objective function in the problem model is a minimum transportation time. Since recovery of a damaged transportation (damaged road in this case) is implied in our problem, the proposed approach has some significant implication to resilience engineering of a service system as well. An example is studied to show the effectiveness of our approach; in particular it is shown that an integrated solution is significantly better than the solution with only the contraflow method.

Keywords

Resilience Service system Design Planning Contraflow Transportation Evacuation 

Notes

Acknowledgements

We thank the financial support to this work by the National Natural Science Foundation of China (NSFC) (Grant No. 71571156), by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. [T32-101/15-R]), by the University of Hong Kong through the Seed Funding Programme for basic research (Grant Nos. 201409159015, 201511159252), and by the open project funded by State Key Laboratory of Synthetical Automation for Process Industries (PAL-N201505) to J. W. Wang and National Science and Engineering Research Council of Canada through a Strategic Project Grant to W. J. Zhang.

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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • J. W. Wang
    • 1
    Email author
  • H. F. Wang
    • 1
    • 2
  • Y. M. Zhou
    • 1
  • Y. Wang
    • 1
  • W. J. Zhang
    • 3
    • 4
  1. 1.Department of Industrial and Manufacturing Systems EngineeringThe University of Hong KongHong KongChina
  2. 2.College of Information Science and EngineeringNortheastern UniversityShenyangChina
  3. 3.Complex Systems Research CenterEast China University of Science and TechnologyShanghaiChina
  4. 4.Department of Mechanical EngineeringUniversity of SaskatchewanSaskatoonCanada

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