资源论文Computational Disaster Management Pascal Van Hentenryck

Computational Disaster Management Pascal Van Hentenryck

2019-11-08 | |  82 |   31 |   0
Abstract Computational Disaster Ma Pascal Optimization Research Grou Computing and Information Systems, Univer1 Introduction The frequency and intensity of natural disasters have been increasing signi?cantly over the past decades and this trend is predicted to continue. Natural disasters have a dramatic impact on human lives and on the socio-economic welfare of entire regions. They were identi?ed in 2011 by the World Bank [The World Bank, 2011] as one of the major risks of the East Asia and Paci?c region, which represents 85 percents of all people affected since 2007. Moreover, this exposure will likely double by 2050 due to rapid urbanization and climate change. To understand the magnitude of such disasters, consider Irene, a category 3 hurricane that hit the East Coast of the United States in August 2011. It killed 56 people, in?icted damages now estimated in the range of 15 billion dollars, and created blackouts that lasted for several days. Hurricane Sandy and the Tohoku tsunami in Japan were even more dramatic, affecting human welfare in entire regions and damaging entire segments of the economy. For instance, Japanese manufacturers lost a signi?cant market shares after the tsunami. It is possible however to mitigate the impact of thesedisasters through appropriate public and corporate policies, investment in infrastructure resilience, real-time decisionsupport systems, and education. In general, the focus of decision-support systems for disaster management is on situational awareness, i.e., communicating to decision makers the siuation in the ?eld as accurately as possible. Situationalawareness is obviously a critical component of any decisionsupport system for disaster management. However, Hurricane Katrina, a traumatic event for the United States, indicated the need to go beyond the communication of timely information; it is critical to enhance the cognitive abilities ofcision makers through advanced use of optimization and simulation technology. The Katrina report [United-States Government, 2006], which should be required reading for policymakers and emergency of?cials around the world, pointed out that “the existing planning and operational structure for delivering critical resources and humanitarian aid clearly proved to be inequate to he task.” In addition, the report rec-ommended that “the Federal government must develop the capacity to conduct large-scale logistical operations”. Similar observations have been made elsewhere: A European am-bassador at a donor conference for Tsunami relief even said that “we do not need another donors’ conference; we need

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