IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i9p5663-d810707.html
   My bibliography  Save this article

Nuclear Accident Emergency Response System: Radiation Field Estimation and Evacuation

Author

Listed:
  • Bo Chen

    (Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China
    Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen 518055, China)

  • Zhicheng Li

    (Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen 518055, China)

  • Zaiyue Yang

    (Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China
    Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen 518055, China)

Abstract

In this paper, a nuclear accident emergency response system based on unmanned aerial vehicles (UAVs) and bus collaboration is designed for radiation field estimation and evacuation. When a nuclear accident occurs, the radiation field is estimated firstly using the measurements acquired by UAVs. Based on the Cramer–Rao Lower Bound (CRLB), the coordinate optimization combined with UAV routing is formulated as a nonconvex mixed integer nonlinear programming (MINLP) problem to maximize the estimation accuracy. Further, a two-stage solution procedure based on genetic algorithm (GA) is proposed to solve the above problem. Then, taking the predicted radiation field as input, personnel in the emergency planning zone (EPZ) are evacuated to shelters by buses. The evacuation routing problem for minimizing both the total radiation exposure and evacuation time is formulated as a mixed integer linear programming (MILP) problem, which is solvable with efficient commercial solvers, such as Gurobi and CPLEX. The simulation results indicate that the system can provide effective help for emergency management under the nuclear accident scenarios.

Suggested Citation

  • Bo Chen & Zhicheng Li & Zaiyue Yang, 2022. "Nuclear Accident Emergency Response System: Radiation Field Estimation and Evacuation," Sustainability, MDPI, vol. 14(9), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5663-:d:810707
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/9/5663/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/9/5663/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Goerigk, Marc & Deghdak, Kaouthar & Heßler, Philipp, 2014. "A comprehensive evacuation planning model and genetic solution algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 82-97.
    2. Antoine G. Hobeika & Sigon Kim & Robert E. Beckwith, 1994. "A Decision Support System for Developing Evacuation Plans around Nuclear Power Stations," Interfaces, INFORMS, vol. 24(5), pages 22-35, October.
    3. Yang Zou & Shuliang Zou & Changming Niu, 2018. "The Optimization of Emergency Evacuation from Nuclear Accidents in China," Sustainability, MDPI, vol. 10(8), pages 1-7, August.
    4. Victor C. Pereira & Douglas R. Bish, 2015. "Scheduling and Routing for a Bus-Based Evacuation with a Constant Evacuee Arrival Rate," Transportation Science, INFORMS, vol. 49(4), pages 853-867, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Qingyi & Wallace, Stein W., 2022. "Non-compliance in transit-based evacuation pick-up point assignments," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    2. Krutein, Klaas Fiete & Goodchild, Anne, 2022. "The isolated community evacuation problem with mixed integer programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    3. Diaz, Rafael & Behr, Joshua G. & Acero, Beatriz, 2022. "Coastal housing recovery in a postdisaster environment: A supply chain perspective," International Journal of Production Economics, Elsevier, vol. 247(C).
    4. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    5. Yushuo Ren & Guoming Zhang & Jianxiang Zheng & Huifang Miao, 2024. "An Integrated Solution for Nuclear Power Plant On-Site Optimal Evacuation Path Planning Based on Atmospheric Dispersion and Dose Model," Sustainability, MDPI, vol. 16(6), pages 1-21, March.
    6. Fatemeh Sabouhi & Ali Bozorgi-Amiri & Mohammad Moshref-Javadi & Mehdi Heydari, 2019. "An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study," Annals of Operations Research, Springer, vol. 283(1), pages 643-677, December.
    7. Ng, ManWo & Diaz, Rafael & Behr, Joshua, 2015. "Departure time choice behavior for hurricane evacuation planning: The case of the understudied medically fragile population," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 215-226.
    8. Shiripour, Saber & Mahdavi-Amiri, Nezam, 2019. "Optimal distribution of the injured in a multi-type transportation network with damage-dependent travel times: Two metaheuristic approaches," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    9. P. Heßler & H. W. Hamacher, 2016. "Sink location to find optimal shelters in evacuation planning," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 325-347, September.
    10. Belton, Valerie & Hodgkin, Julie, 1999. "Facilitators, decision makers, D.I.Y. users: Is intelligent multicriteria decision support for all feasible or desirable?," European Journal of Operational Research, Elsevier, vol. 113(2), pages 247-260, March.
    11. Moshtagh, Mehrdad & Fathali, Jafar & Smith, J. MacGregor, 2018. "The Stochastic Queue Core problem, evacuation networks, and state-dependent queues," European Journal of Operational Research, Elsevier, vol. 269(2), pages 730-748.
    12. Bretschneider, S. & Kimms, A., 2011. "A basic mathematical model for evacuation problems in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 523-539, July.
    13. Dean, Matthew D. & Nair, Suresh K., 2014. "Mass-casualty triage: Distribution of victims to multiple hospitals using the SAVE model," European Journal of Operational Research, Elsevier, vol. 238(1), pages 363-373.
    14. Seunghyun Choi & Jonggil Chae & Myungsik Do, 2022. "Emergency Road Network Determination for Seoul Metropolitan Area," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    15. Zhao, Xing & Ji, Kang & Xu, Peng & Qian, Wen-wen & Ren, Gang & Shan, Xiao-nian, 2020. "A round-trip bus evacuation model with scheduling and routing planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 285-300.
    16. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    17. Bian Liang & Dapeng Yang & Xinghong Qin & Teresa Tinta, 2019. "A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    18. Yuanyuan Feng & Yi Cao & Shuanghua Yang & Lili Yang & Tangjian Wei, 2023. "A two-step sub-optimal algorithm for bus evacuation planning," Operational Research, Springer, vol. 23(2), pages 1-35, June.
    19. Cui, Geng & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2021. "Incorporating genetic algorithm to optimise initial condition of pedestrian evacuation based on agent aggressiveness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    20. Huan Cao & Tian Li & Shuxia Li & Tijun Fan, 2017. "An integrated emergency response model for toxic gas release accidents based on cellular automata," Annals of Operations Research, Springer, vol. 255(1), pages 617-638, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5663-:d:810707. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.