RESilient Emergency Preparedness for Natural Disaster Response through Operational Research(RESPOND-OR)

Lead Research Organisation: Lancaster University
Department Name: Management Science

Abstract

Natural disasters have grave consequences for human, social and economic environment. Although large-scale natural disasters occur worldwide, statistical evidence suggests that their negative impacts are much more pronounced in less developed countries. Between 2003-2013, natural disasters in developing countries cost about $550 billion and affected 2 billion people. Indonesia and Sudan are among the countries enormously affected by the economic and societal consequences of natural disasters. In Indonesia, a natural disaster may trigger another natural disaster, either simultaneously or in a sequential order. In addition, the disaster response in Indonesia needs to take into consideration the archipelago structure of the country. In Sudan, the prevalent disaster, which is flooding may trigger a health emergency that requires simultaneous consideration. Furthermore, the disaster response operations in Sudan are characterized by high risk due to civil conflicts.
The optimization of disaster preparedness and response interventions provides ample potential to decrease the magnitude of the negative impacts of the disasters with significant economic and societal benefits for the sustainability of the impacted communities. However, available approaches are mostly based on generic assumptions that tend to oversimplify the decision-making needs of disaster management agencies. Specifically, available disaster preparedness and response models do not adequately address the following challenges:

1. Modelling of the allocation of disaster response resources for combined large-scale natural disasters that happen simultaneously and/or sequentially, i.e. earthquakes triggering tsunamis, or outbreak of diseases following floods.

2. Integrated modelling of strategic disaster preparedness and operational disaster relief decisions.

3. Modelling the routing and scheduling of humanitarian support resources in the presence of civil disobedience and social conflict.

4. The incorporation of fairness criteria in modelling disaster preparedness and response decisions.

The lack of models capturing the real world complexities leads to inefficient allocation and use of scarce disaster preparedness and response resources. Therefore, there is an urgent need to address the mathematical modelling and associated computational and data management challenges stemming from the complexity of the real world decision-making environment of disaster management agencies. The RESPOND-OR project will develop the next generation of models which will incorporate the requirements of all relevant stakeholders. The complexity of the proposed models will necessitate the development of new hyper heuristics that will provide good quality solutions in very short computational times.

The mathematical models, the solution algorithms, and the data management and visualization tools will underpin the development of a Decision Support System (DSS) that will enhance the decision-making capabilities of disaster preparedness and response organizations in Indonesia and Sudan. The research team has an internationally leading profile in the areas of mathematical modelling, heuristic development, stochastic optimization, data management and visualization, and disaster preparedness and response management. The research team has an excellent record in stakeholder engagement. We will work very closely with our stakeholder partners to ensure that the outcome of RESPOND-OR will be scientifically sound and fully aligned with their needs.

Planned Impact

The strategic vision of the RESPOND-OR project is to develop and implement cutting edge mathematical models and solution algorithms that will underpin the development of a Decision Support System (DSS) for disaster preparedness and response in Indonesia and Sudan. The emphasis is on both the development and use of the proposed DSS. This will have a tremendous economic and societal impact by enabling more efficient and effective allocation and use of the available disaster preparedness and response resources. The proposed research is addressing an important issue that affects the sustainability of communities located in disaster-prone areas. The project results will impact the following stake holding groups: i) disaster preparedness and response organizations, ii) policy makers, iii) research communities, and iv) general public. In what follows we discuss the project impacts on the identified stake holding groups.

(i) Disaster Preparedness and Response organizations: Disaster preparedness and response involve both governmental and non-governmental organizations. The DSS that will be developed by the RESPOND-OR project will help these organizations to optimise the allocation of their emergency preparedness resources. For instance, the optimization of the resilience of critical infrastructure networks such as the transport network, will contribute to the reduction of the disaster damages, and will increase the efficiency of population evacuation operations. The optimum routing, rostering and scheduling of humanitarian assistance and emergency response volunteers will increase the timeliness of disaster response.

(ii) Policy Makers: In Indonesia and Sudan disaster preparedness and response is high in the policy agenda. Both governments need to investigate policy options for ensuring the sustainability of communities located in disaster prone areas. The proposed DSS will allow policy makers to analyse trade-offs regarding the efficiency and fairness of their disaster preparedness and response policies. Furthermore, the proposed DSS will support post action assessment, which can inform potential changes on the way government allocates disaster management resources. The results of these assessments will ultimately influence governmental policies.

(iii) Research Communities: The proposed research will contribute to the advancement of knowledge in the fields of Operational Research, Mathematics, Data Science, Computational Science, Information Systems, and disaster preparedness and response. The results of the RESPOND-OR project will improve the mathematical understanding of complex disaster preparedness and response problems.

(iv) General Public: This research has the potential to generate significant social and economic impact of people living in disaster-prone areas. The development of models for improved disaster preparedness and response through coordinated and targeted prevention and recovery activities, and resourceful disaster response will reduce the disruption of the socio-economic activities of the affected communities.

Publications

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