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Graham Coates, Glenn I. Hawe, Duncan T. Wilson, & Roger S. Crouch. (2011). Adaptive co-ordinated emergency response to rapidly evolving large-scale unprecedented events (REScUE). In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents an overview of ongoing research into the development of an integrated framework aimed at adaptive co-ordination of emergency response to dynamic, fast evolving and novel events on a large-scale. The framework consists of (i) a decision support system, supported by rapid adaptive search methods, to enable the real time development of tailored response plans including emergency responder team composition and task allocation to these teams, and (ii) an agent-based simulation of emergency response to large-scale events occurring in real geographical locations. The aim of this research is to contribute to understanding how better agent-based simulation coupled with decision support can be used to enable the effective co-ordination of emergency response, involving the collective efforts and actions of multiple agencies (ambulance services, fire brigades, police forces and emergency planning units), to rapidly evolving large-scale unprecedented events.
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Haya Aldossary, & Graham Coates. (2019). A Preliminary Optimisation-based Approach to Coordinate the Response of Ambulances in Mass Casualty Incidents. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Mass Casualty Incidents (MCIs) may occur with no notice and require a rapid response to manage the casualties and arrange their transportation to hospitals. MCIs may result in different numbers of casualties and fatalities. Further, response time can play a crucial role in reducing fatalities and protecting lives. This paper reports on a preliminary optimisation-based approach, termed MCIER, which has been developed to co-ordinate the response of ambulances to multiple MCIs. In this approach, a realistic representation of the road network is modelled for the geographical area of interest. Also, a Neighbourhood Search Algorithm (NSA) has been developed in order to find the optimum solution to the problem under consideration. A hypothetical case study of a MCI in Newcastle-upon-Tyne has been considered to investigate the effect on response time of the time of day, and day of week, on which the incident occurs.
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Haya Aldossary, & Graham Coates. (2021). Multi-objective Optimization for Coordinating Emergency Resources in Multiple Mass Casualty Incidents. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 1015–1027). Blacksburg, VA (USA): Virginia Tech.
Abstract: Effective co-ordination between resource-constrained emergency services during multiple mass casualty incidents (MCIs) plays a significant role in the response phase. In such a case, the co-ordination problem needs to be solved, namely the allocation of responders-to-incidents, responders-to-casualties, vehicles to travel to casualties at incidents and transport casualties to hospitals, and task assignment to responders and vehicles. A Neighborhood Search Algorithm (NSA) is employed to solve the co-ordination problem with the aim of reducing the suffering of casualties, with varying injuries and health classifications. An application of the NSA is enabled using a hypothetical case study of MCIs including three scenarios in a major urban area of the UK. The experiments conducted show the effectiveness of using different approaches to generate an initial response plan, and the performance of the NSA in developing a final optimized plan.
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