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A hybrid and integrated approach to evaluate and prevent disasters

Author

Listed:
  • Alessio Ishizaka

    (University of Portsmouth, Portsmouth, UK)

  • Ashraf Labib

    (University of Portsmouth, Portsmouth, UK)

Abstract

Disasters are, by their nature, very complex phenomena. Their modelling using a systematic and logical methodology can help us identify their root causes and may facilitate in allocating appropriate resources to prevent such situations. Although techniques exist to model such phenomena, a single off-the-shelf model is insufficient to provide an effective and realistic analysis to prevent disasters due to its inherent assumptions. In order to overcome these limitations of single methods, this article proposes a hybrid model of four methods to optimise a safety investment. First, a hierarchy is constructed with a problem structuring approach. Second, a new graphical representation, the Crisis Tree Analysis, is introduced to visualise how a combination of basic events may lead to a disaster. Third, the criticality of each event is assessed using the Analytic Hierarchy Process. Finally, a mathematical programming model is proposed to calculate the optimal allocation of available funds in order to avoid the disaster. A case study of the Bhopal disaster is used to illustrate the proposed four-step method.

Suggested Citation

  • Alessio Ishizaka & Ashraf Labib, 2014. "A hybrid and integrated approach to evaluate and prevent disasters," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(10), pages 1475-1489, October.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:10:p:1475-1489
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    Citations

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    Cited by:

    1. Lai, Yi-Ling & Ishizaka, Alessio, 2020. "The application of multi-criteria decision analysis methods into talent identification process: A social psychological perspective," Journal of Business Research, Elsevier, vol. 109(C), pages 637-647.
    2. Maria Cerreta & Giuliano Poli, 2017. "Landscape Services Assessment: A Hybrid Multi-Criteria Spatial Decision Support System (MC-SDSS)," Sustainability, MDPI, vol. 9(8), pages 1-18, July.
    3. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    4. Wang, Fang & Gao, Yue & Dong, Wenxu & Li, Zhiwei & Jia, Xiaoping & Tan, Raymond R., 2017. "Segmented pinch analysis for environmental risk management," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 353-361.
    5. Bhuvnesh Sharma & M. Ramkumar & Nachiappan Subramanian & Bharat Malhotra, 2019. "Dynamic temporary blood facility location-allocation during and post-disaster periods," Annals of Operations Research, Springer, vol. 283(1), pages 705-736, December.
    6. Yuji Sato & Kim Hua Tan, 2023. "Inconsistency indices in pairwise comparisons: an improvement of the Consistency Index," Annals of Operations Research, Springer, vol. 326(2), pages 809-830, July.
    7. Ho, William & Ma, Xin, 2018. "The state-of-the-art integrations and applications of the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 267(2), pages 399-414.

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