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A Knowledge-Based Multi-Criteria Decision Support System Encompassing Cascading Effects for Disaster Management

Author

Listed:
  • Brunella Caroleo

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Enrico Palumbo

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Michele Osella

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Antonio Lotito

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Giuseppe Rizzo

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Enrico Ferro

    (Istituto Superiore Mario Boella (ISMB), Via P. C. Boggio 61, Turin, 10138, Italy)

  • Antonio Attanasio

    (Politecnico di Torino, Department of Control and Computing Engineering, Corso Duca Degli Abruzzi 24, Turin 10129, Italy)

  • Silvia Chiusano

    (Politecnico di Torino, Department of Control and Computing Engineering, Corso Duca Degli Abruzzi 24, Turin 10129, Italy)

  • Giulio Zuccaro

    (Università di Napoli Federico II, LUPT-PLINIVS Study Centre, Via Toledo 402, Naples 80134, Italy)

  • Mattia Leone

    (Università di Napoli Federico II, LUPT-PLINIVS Study Centre, Via Toledo 402, Naples 80134, Italy)

  • Daniela De Gregorio

    (Università di Napoli Federico II, LUPT-PLINIVS Study Centre, Via Toledo 402, Naples 80134, Italy)

Abstract

This paper describes a knowledge-based decision support system (KB-DSS) to improve the preparedness of crisis situations induced by natural and technological hazards. The proposed KB-DSS aims to manage the potential cascading effects generated by a triggering hazard assessing the possible event time histories based on interconnected probabilistic simulation models. From a methodological point of view, a decision model based on two Multi-Criteria Decision-Making (MCDM) algorithms follows a cascading effect simulation model. This combination allows to support the decision maker in comparing a set of mitigation strategies on the basis of their expected impacts and his priorities. The algorithm is based on an ensemble approach, which combines decisions over an array of possible impact scenarios, instead of only relying on the average impact scenario. An application of the KB-DSS to the case of a possible reactivation of Nea Kameni volcano in Santorini is presented to show how the proposed architecture could be applied to a real case. The proposed methodology supports the emergency planners in making the best decisions supporting them also in the choice of the best timing for the intervention.

Suggested Citation

  • Brunella Caroleo & Enrico Palumbo & Michele Osella & Antonio Lotito & Giuseppe Rizzo & Enrico Ferro & Antonio Attanasio & Silvia Chiusano & Giulio Zuccaro & Mattia Leone & Daniela De Gregorio, 2018. "A Knowledge-Based Multi-Criteria Decision Support System Encompassing Cascading Effects for Disaster Management," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(05), pages 1469-1498, September.
    • Handle: RePEc:wsi:ijitdm:v:17:y:2018:i:05:n:s021962201850030x
    DOI: 10.1142/S021962201850030X
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    References listed on IDEAS

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    1. Rafael Marin & Pollyana Notargiacomo, 2021. "Multiagent Intelligent Tutoring System for Financial Literacy," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global, vol. 17(7), pages 1-13, November.
    2. Giulio Zuccaro & Daniela De Gregorio & Mattia Federico Leone & Salvatore Sessa & Stefano Nardone & Francesca Linda Perelli, 2021. "CAESAR II Tool: Complementary Analyses for Emergency Planning Based on Seismic Risks Impact Evaluations," Sustainability, MDPI, vol. 13(17), pages 1-20, September.

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