Natural events, climate change and urbanization are pushing the pressure on disaster relief operations. Decision science and ICT technologies can be effectively used to face humanitarian logistics issues. This concerns both manmade threats (accidents) and natural hazards such as e.g. floods, storms, earthquakes and volcanic eruptions. The purpose of this paper is to analyse the operation strategies for rescue in emergency situations deployed by specialized rescue teams. Usually standard procedures are applied for rescue operations. These procedures can fail in disaster relief situations where an abnormal number of rescue operations are to be fulfilled. It is important to study mechanisms able to give more flexibility to these procedures and to study the effectiveness of the procedures in planning phase. At this aim we used discrete event simulation as decision support for planning different strategies of action to apply in emergency and risk situations. In particular several scenarios have been developed as simulation models combining different initial hypothesis with the aim to build a generalized and flexible procedure to apply in different scenarios. As a result, the simulation is able to allocate efficiently different resources under emergency situations (multiple scenarios for specific events). Tests and sensitivity analysis have been performed using instances related to a GIS of the Italian Sicily region and a typical set of facilities and rescue team. The simulation system works considering the different typologies of vehicles and staff to choose the best solution available in that specific time. The work is part of a national research project aimed to develop cloud-based systems and sensor networks for multi-risk management. The developed simulation system can provide crucial help to the rescuers in order to planning the best relief strategy for mitigate the effects of natural and industrial disasters.

A Simulation study of logistics for disaster relief operations

Antonio D'Uffizi;Marco Simonetti;Giuseppe Stecca;Giuseppe Confessore
2015

Abstract

Natural events, climate change and urbanization are pushing the pressure on disaster relief operations. Decision science and ICT technologies can be effectively used to face humanitarian logistics issues. This concerns both manmade threats (accidents) and natural hazards such as e.g. floods, storms, earthquakes and volcanic eruptions. The purpose of this paper is to analyse the operation strategies for rescue in emergency situations deployed by specialized rescue teams. Usually standard procedures are applied for rescue operations. These procedures can fail in disaster relief situations where an abnormal number of rescue operations are to be fulfilled. It is important to study mechanisms able to give more flexibility to these procedures and to study the effectiveness of the procedures in planning phase. At this aim we used discrete event simulation as decision support for planning different strategies of action to apply in emergency and risk situations. In particular several scenarios have been developed as simulation models combining different initial hypothesis with the aim to build a generalized and flexible procedure to apply in different scenarios. As a result, the simulation is able to allocate efficiently different resources under emergency situations (multiple scenarios for specific events). Tests and sensitivity analysis have been performed using instances related to a GIS of the Italian Sicily region and a typical set of facilities and rescue team. The simulation system works considering the different typologies of vehicles and staff to choose the best solution available in that specific time. The work is part of a national research project aimed to develop cloud-based systems and sensor networks for multi-risk management. The developed simulation system can provide crucial help to the rescuers in order to planning the best relief strategy for mitigate the effects of natural and industrial disasters.
2015
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
Istituto di Cristallografia - IC
Logistics
Simulation
Operation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/227357
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