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A Decision-Making Algorithm for Maritime Search and Rescue Plan

Author

Listed:
  • Donatien Agbissoh OTOTE

    (College of Geomatics, Shandong University of Science and Technology, Qianwangang Road, Huangdao Zone, Qingdao 266590, China)

  • Benshuai Li

    (College of Geomatics, Shandong University of Science and Technology, Qianwangang Road, Huangdao Zone, Qingdao 266590, China)

  • Bo Ai

    (College of Geomatics, Shandong University of Science and Technology, Qianwangang Road, Huangdao Zone, Qingdao 266590, China)

  • Song Gao

    (North China Sea Marine Forecasting Center of State Oceanic Administration, Qingdao 266590, China)

  • Jing Xu

    (College of Geomatics, Shandong University of Science and Technology, Qianwangang Road, Huangdao Zone, Qingdao 266590, China)

  • Xiaoying Chen

    (Hubei Provincial Information Center, No.17, Fruit Lake East 1st Road, Wuchang Zone, Wuhan 430071, China)

  • Guannan Lv

    (College of Geomatics, Shandong University of Science and Technology, Qianwangang Road, Huangdao Zone, Qingdao 266590, China
    Qingdao Yuehai Information Service Co, Ltd., Qingdao 266590, China)

Abstract

With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based on the optimal search theory. It also analyzes three important concepts: Probability of containment (POC), probability of detection (POD), and probability of success (POS) involved in the maritime search and rescue decision-making process. In this paper, the calculation methods of POC and POD variables have been improved, and the search success rate has been improved to some extent. Finally, an example analysis of the maritime search and rescue incident is given. Through verification, the algorithm proposed in this paper can support maritime search and rescue decisions.

Suggested Citation

  • Donatien Agbissoh OTOTE & Benshuai Li & Bo Ai & Song Gao & Jing Xu & Xiaoying Chen & Guannan Lv, 2019. "A Decision-Making Algorithm for Maritime Search and Rescue Plan," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:7:p:2084-:d:220831
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    References listed on IDEAS

    as
    1. Abi-Zeid, Irene & Frost, John R., 2005. "SARPlan: A decision support system for Canadian Search and Rescue Operations," European Journal of Operational Research, Elsevier, vol. 162(3), pages 630-653, May.
    2. Henry R. Richardson & Joseph H. Discenza, 1980. "The United States Coast Guard Computer‐Assisted Search Planning system (CASP)," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 27(4), pages 659-680, December.
    3. Bernard O. Koopman, 1957. "The Theory of Search," Operations Research, INFORMS, vol. 5(5), pages 613-626, October.
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    Cited by:

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    2. Mariusz Jacewicz & Marcin Żugaj & Robert Głębocki & Przemysław Bibik, 2022. "Quadrotor Model for Energy Consumption Analysis," Energies, MDPI, vol. 15(19), pages 1-33, September.

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