Decision Support for Crisis & Disaster Operations
Course duration: 10 h
Recent natural and man-made disasters affected many parts of the world and resulted in an extensive loss of life, disruption of infrastructure and significant economic impacts to regional and national economies. The randomness of impacts and the urgency of response efforts are challenging the operational analyst and demand a dynamic decision-making in an uncertain and complex environment. A far-sighted and comprehensive emergency planning in the pre-disaster phase can help to alleviate the effects of a suddenly arising critical event. Methods from computational intelligence and sophisticated agent-based simulation systems allow a detailed risk analysis and an evaluation of the vulnerability of infrastructures and supply systems. Major disasters require a cross-organizational coordination of relief activities that are usually concerned with the limited availability of resources and infrastructure to address the needs of the affected population. Integrated decision support systems and Operations Research tools enable an efficient coordination of rescue and facilitate further disaster relief activities.
In this course, we will discuss how modern Operational Research can support the operational analyst in the pre-disaster planning phase as well as the post-disaster response phase. In particular, we will address selected problems in the fields of
- city evacuation planning
- vehicle routing
- facility location problems
- humanitarian supply chains
- early warning systems.
Prof. Erik Kropat
Place of employment: Bundeswehr University Munich / ITIS, Institute for Theoretical Computer Science, Mathematics and Operations Research, Munich, Germany.
Spheres of researches: Operations Research; identification and optimization of complex networks under uncertainty in technology, finance and computational biology; gene-environment networks; eco-finance-networks; homogenization theory of differential equations on networks; spatial data mining; web mining; fuzzy theory; fuzzy data mining and fuzzy decision support systems.