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Models and computational algorithms for maritime risk analysis: a review

Author

Listed:
  • Gino J. Lim

    (University of Houston)

  • Jaeyoung Cho

    (Lamar University)

  • Selim Bora

    (Texas A&M University at Qatar)

  • Taofeek Biobaku

    (University of Houston)

  • Hamid Parsaei

    (Texas A&M University at Qatar)

Abstract

Due to the undesirable implications of maritime mishaps such as ship collisions and the consequent damages to maritime property; the safety and security of waterways, ports and other maritime assets are of the utmost importance to authorities and researches. Terrorist attacks, piracy, accidents and environmental damages are some of the concerns. This paper provides a detailed literature review of over 180 papers about different threats, their consequences pertinent to the maritime industry, and a discussion on various risk assessment models and computational algorithms. The methods are then categorized into three main groups: statistical, simulation and optimization models. Corresponding statistics of papers based on year of publication, region of case studies and methodology are also presented.

Suggested Citation

  • Gino J. Lim & Jaeyoung Cho & Selim Bora & Taofeek Biobaku & Hamid Parsaei, 2018. "Models and computational algorithms for maritime risk analysis: a review," Annals of Operations Research, Springer, vol. 271(2), pages 765-786, December.
    • Handle: RePEc:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-018-2768-4
    DOI: 10.1007/s10479-018-2768-4
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    Cited by:

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    4. Ramos, M.A. & Thieme, Christoph A. & Utne, Ingrid B. & Mosleh, A., 2020. "Human-system concurrent task analysis for maritime autonomous surface ship operation and safety," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Mazurek, J. & Lu, L. & Krata, P. & Montewka, J. & Krata, H. & Kujala, P., 2022. "An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Dinis, D. & Teixeira, A.P. & Guedes Soares, C., 2020. "Probabilistic approach for characterising the static risk of ships using Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

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