IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v93y2008i7p940-949.html
   My bibliography  Save this article

Modelling the reliability of search and rescue operations with Bayesian Belief Networks

Author

Listed:
  • Norrington, Lisa
  • Quigley, John
  • Russell, Ashley
  • Van der Meer, Robert

Abstract

This paper uses a Bayesian Belief Networks (BBN) methodology to model the reliability of Search And Rescue (SAR) operations within UK Coastguard (Maritime Rescue) coordination centres. This is an extension of earlier work, which investigated the rationale of the government's decision to close a number of coordination centres. The previous study made use of secondary data sources and employed a binary logistic regression methodology to support the analysis. This study focused on the collection of primary data through a structured elicitation process, which resulted in the construction of a BBN. The main findings of the study are that statistical analysis of secondary data can be used to complement BBNs. The former provided a more objective assessment of associations between variables, but was restricted in the level of detail that could be explicitly expressed within the model due to a lack of available data. The latter method provided a much more detailed model, but the validity of the numeric assessments was more questionable. Each method can be used to inform and defend the development of the other. The paper describes in detail the elicitation process employed to construct the BBN and reflects on the potential for bias.

Suggested Citation

  • Norrington, Lisa & Quigley, John & Russell, Ashley & Van der Meer, Robert, 2008. "Modelling the reliability of search and rescue operations with Bayesian Belief Networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 940-949.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:7:p:940-949
    DOI: 10.1016/j.ress.2007.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832007001032
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2007.03.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lee, Chang-Ju & Lee, Kun Jai, 2006. "Application of Bayesian network to the probabilistic risk assessment of nuclear waste disposal," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 515-532.
    2. R B van der Meer & J Quigley & J E Storbeck, 2005. "Using data envelopment analysis to model the performance of UK coastguard centres," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 889-901, August.
    3. Celeux, G. & Corset, F. & Lannoy, A. & Ricard, B., 2006. "Designing a Bayesian network for preventive maintenance from expert opinions in a rapid and reliable way," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 849-856.
    4. R B Van der Meer & J Quigley & J E Storbeck, 2005. "Using regression analysis to model the performance of UK Coastguard centres," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 630-641, June.
    5. Jason R. W. Merrick & J. René van Dorp & Thomas Mazzuchi & John R. Harrald & John E. Spahn & Martha Grabowski, 2002. "The Prince William Sound Risk Assessment," Interfaces, INFORMS, vol. 32(6), pages 25-40, December.
    6. Quigley, John & Bedford, Tim & Walls, Lesley, 2007. "Estimating rate of occurrence of rare events with empirical bayes: A railway application," Reliability Engineering and System Safety, Elsevier, vol. 92(5), pages 619-627.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Yue & Feng, Qiang & Fan, Dongming & Ren, Yi & Sun, Bo & Yang, Dezhen & Wang, Zili, 2023. "Optimization of maritime support network with relays under uncertainty: A novel matheuristics method," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    2. Misuri, Alessio & Landucci, Gabriele & Cozzani, Valerio, 2020. "Assessment of safety barrier performance in Natech scenarios," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    4. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    5. Ricci, Federica & Yang, Ming & Reniers, Genserik & Cozzani, Valerio, 2024. "Emergency response in cascading scenarios triggered by natural events," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    6. Marhavilas, P.K. & Koulouriotis, D.E., 2012. "A combined usage of stochastic and quantitative risk assessment methods in the worksites: Application on an electric power provider," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 36-46.
    7. Burciu, Zbigniew & Grabski, Franciszek, 2011. "The experimental and theoretical study of life raft safety under strong wind," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1456-1461.
    8. Zhang, D. & Yan, X.P. & Yang, Z.L. & Wall, A. & Wang, J., 2013. "Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 93-105.
    9. Abroon Qazi & Mecit Can Emre Simsekler & Steven Formaneck, 2023. "Supply chain risk network value at risk assessment using Bayesian belief networks and Monte Carlo simulation," Annals of Operations Research, Springer, vol. 322(1), pages 241-272, March.
    10. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    11. Jinfen Zhang & Ângelo P Teixeira & C. Guedes Soares & Xinping Yan & Kezhong Liu, 2016. "Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1171-1187, June.
    12. Qazi, Abroon & Quigley, John & Dickson, Alex & Ekici, Şule Önsel, 2017. "Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies," European Journal of Operational Research, Elsevier, vol. 259(1), pages 189-204.

    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. Gligor, David & Bozkurt, Siddik, 2020. "FsQCA versus regression: The context of customer engagement," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    2. Burciu, Zbigniew & Grabski, Franciszek, 2011. "The experimental and theoretical study of life raft safety under strong wind," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1456-1461.
    3. Mumtaz Karatas & Nasuh Razi & Murat M. Gunal, 2017. "An ILP and simulation model to optimize search and rescue helicopter operations," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1335-1351, November.
    4. N C Simpson & P G Hancock, 2009. "Fifty years of operational research and emergency response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 126-139, May.
    5. Skarmeas, Dionysis & Leonidou, Constantinos N. & Saridakis, Charalampos, 2014. "Examining the role of CSR skepticism using fuzzy-set qualitative comparative analysis," Journal of Business Research, Elsevier, vol. 67(9), pages 1796-1805.
    6. Urueña, Alberto & Hidalgo, Antonio, 2016. "Successful loyalty in e-complaints: FsQCA and structural equation modeling analyses," Journal of Business Research, Elsevier, vol. 69(4), pages 1384-1389.
    7. Rafic Faddoul & Wassim Raphael & Abdul-Hamid Soubra & Alaa Chateauneuf, 2013. "Incorporating Bayesian networks in Markov Decision Processes," Post-Print hal-01006963, HAL.
    8. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    9. Jason R. W. Merrick & Claire A. Dorsey & Bo Wang & Martha Grabowski & John R. Harrald, 2022. "Measuring Prediction Accuracy in a Maritime Accident Warning System," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 819-827, February.
    10. Keisuke Himoto, 2020. "Hierarchical Bayesian Modeling of Post‐Earthquake Ignition Probabilities Considering Inter‐Earthquake Heterogeneity," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1124-1138, June.
    11. Montewka, Jakub & Hinz, Tomasz & Kujala, Pentti & Matusiak, Jerzy, 2010. "Probability modelling of vessel collisions," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 573-589.
    12. Suyi Li & Qiang Meng & Xiaobo Qu, 2012. "An Overview of Maritime Waterway Quantitative Risk Assessment Models," Risk Analysis, John Wiley & Sons, vol. 32(3), pages 496-512, March.
    13. Xie, Shuyi & Huang, Zimeng & Wu, Gang & Luo, Jinheng & Li, Lifeng & Ma, Weifeng & Wang, Bohong, 2024. "Combining precursor and Cloud Leaky noisy-OR logic gate Bayesian network for dynamic probability analysis of major accidents in the oil depots," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    14. John Quigley & Kevin J. Wilson & Lesley Walls & Tim Bedford, 2013. "A Bayes Linear Bayes Method for Estimation of Correlated Event Rates," Risk Analysis, John Wiley & Sons, vol. 33(12), pages 2209-2224, December.
    15. Goerlandt, Floris & Montewka, Jakub, 2015. "Maritime transportation risk analysis: Review and analysis in light of some foundational issues," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 115-134.
    16. J Montewka & P Krata & F Goerlandt & A Mazaheri & P Kujala, 2011. "Marine traffic risk modelling – an innovative approach and a case study," Journal of Risk and Reliability, , vol. 225(3), pages 307-322, September.
    17. Tan, Tu Guang & Jang, Sunghyon & Yamaguchi, Akira, 2019. "A novel method for risk-informed decision-making under non-ideal Instrumentation and Control conditions through the application of Bayes’ Theorem," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 463-472.
    18. Hongyang Yu & Faisal Khan & Brian Veitch, 2017. "A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1668-1682, September.
    19. Zhang, Weibin & Feng, Xinyu & Goerlandt, Floris & Liu, Qing, 2020. "Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    20. Zheng, Yi-Xuan & Xiahou, Tangfan & Liu, Yu & Xie, Chaoyang, 2021. "Structure function learning of hierarchical multi-state systems with incomplete observation sequences," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

    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:eee:reensy:v:93:y:2008:i:7:p:940-949. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.