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Methodological Proposal for Optimal Location of Emergency Operation Centers through Multi-Criteria Approach

Author

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  • Umberto Di Matteo

    (Department of Engineering Sustainability, Marconi University, Rome 00186, Italy)

  • Priscilla Maria Pezzimenti

    (Department of Engineering Sustainability, Marconi University, Rome 00186, Italy)

  • Davide Astiaso Garcia

    (DIAEE-Department of Astronautic, Energetic and Electric Engineering, Sapienza University, Rome 00185, Italy)

Abstract

Territorial vulnerability and risk analysis play a fundamental role in urban planning and emergency management. Requirements analysis of such aspects are possible to define more and more effective risk mitigation strategies providing efficient response plans to events. Many mitigation strategies as well as many response plans have in common the purpose of minimizing response time in order to decrease the level of vulnerability of the concerning area. The response time to a perturbing event is in fact an essential parameter to define the hazard of the considered site and literature is unanimous in considering it. In this context, the article proposes a methodology for the optimization of the location on the territory of emergency operation centers (EOCs), reducing response times and mitigating in this way the vulnerability of the area. The proposed methodology is based on a multi-criteria decision making (MCDM) hybrid type AHP (Analytic Hierarchy Process)-Electre. This method has been applied in the territory of Bressanone and Vipiteno (Bolzano-Italy), simulating the need to build a new barrack of Fire Department. A campaign of interviews with operators and industry experts and the collection of spatial data from the portals of the concerned authorities has been carried out in order to get the number of necessary data for the implementation of the proposed methodology.

Suggested Citation

  • Umberto Di Matteo & Priscilla Maria Pezzimenti & Davide Astiaso Garcia, 2016. "Methodological Proposal for Optimal Location of Emergency Operation Centers through Multi-Criteria Approach," Sustainability, MDPI, vol. 8(1), pages 1-12, January.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:1:p:50-:d:61813
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    References listed on IDEAS

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    2. Sánchez-Lozano, Juan M. & Teruel-Solano, Jerónimo & Soto-Elvira, Pedro L. & Socorro García-Cascales, M., 2013. "Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 544-556.
    3. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
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    Cited by:

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    2. Umberto Di Matteo & Sofia Agostinelli, 2022. "Big Data Analysis for Optimising the Decision-Making Process in Sustainable Energy Action Plans: A Multi-Criteria Evaluation Approach Applied to Sicilian Regional Recovery and Resilience Plans," Energies, MDPI, vol. 15(20), pages 1-22, October.
    3. Gawlik Remigiusz & Głuszak Michał & Małkowska Agnieszka, 2017. "The Measurement of Housing Preferences in the Analytic Hierarchy Process," Folia Oeconomica Stetinensia, Sciendo, vol. 17(1), pages 31-43, June.
    4. Beniamino Murgante & Mohamad Salmani & Mohamad Molaei Qelichi & Mehdi Hajilo, 2017. "A Multiple Criteria Decision-Making Approach to Evaluate the Sustainability Indicators in the Villagers’ Lives in Iran with Emphasis on Earthquake Hazard: A Case Study," Sustainability, MDPI, vol. 9(8), pages 1-14, August.
    5. Violeta Dimić & Mimica Milošević & Dušan Milošević & Dragan Stević, 2018. "Adjustable Model of Renewable Energy Projects for Sustainable Development: A Case Study of the Nišava District in Serbia," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    6. Gawlik, Remigiusz, 2016. "Stratyfikacja próby badawczej i dobór ekspertów na przykładzie modelu decyzyjnego opartego na metodzie AHP [Stratification of research target group and selection of experts for AHP based decision m," MPRA Paper 74690, University Library of Munich, Germany.

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