Dynamic Programming Applied to Disaster Relief Response

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With the widespread, expensive, and life-threatening damage that can occur during natural disasters, including floods, wildfires, earthquakes, and other events, it is important that the responses to these events are quick and performed efficiently, with cost and resource optimization in mind. That way, resources are not wasted in areas that don’t need them. And, if this were to happen, other, high-demand areas would suffer. With the amount of damage and displacement of local populations that occur, the planning and deployment of nearby resources needs to address these concerns. If done poorly, poor planning can in fact work against its own goals and cause failures to occur that compromise millions in assets and endanger many people as well. Take, for example, the legendary failure of FEMA in its response to Hurricane Katrina. Yes, one of the main reasons that FEMA failed was its inability to gather resources and knowledge, but it also lacked the ability to mobilize its resources (whereas Walmart could do both of these things successfully) (Horwitz 1). Utilizing a dynamic programming approach to deploy resources in specific areas based on what is available could vastly improve the effectiveness of a response plan. It may seem simple; if a resource were needed in an area, then one should send it there. However, there are millions of ways to distribute a resource to obtain an optimal value, and the optimal value changes based on the series of decisions made. In a computer system, it will take too long to calculate all of the combinations in order to find the optimal combination of resource allocation that can both save lives/assets as well as lower costs. To begin with, it is important to explain the concept of a dynamic optimiz... ... middle of paper ... ...to coordinate their supplier networks with known information about the status of a disaster in some regions. Works Cited Horwitz, Steven. "FEMA Doesn't Have Local Knowledge Needed for Effective Relief." Mercatus Center: George Mason University. Mercatus Center, 01 Nov. 2013. Web. 28 Nov. 2013. . Su, Xiaohui et al. The Study on Optimal Model for Relief Resources Allocation Using Dynamic Programming and Spatial Analysis Methods. Rep. GiScience/People's Republic of China, n.d. Web. 27 Nov. 2013. giscience2012_paper_184.pdf>. Wiitala, Marc R. "A dynamic programming approach to determining optimal forest wildfire initial attack responses." Fire Economics, Planning, and Policy: Bottom Lines (1999): 115-123.

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