A need exists to develop a software simulation that demonstrates the most effective methods of evacuation for disaster scenarios. In a real-world situation this heuristic coupled with real-time data gathered by sensors could serve to provide an efficient rescue plan. Data gathered about the terrain in the immediate aftermath of the situation is invaluable in deciding a plan of action. With this type of information many different routes can be planned so that recovery or rescue can be made as optimal as possible. But of course in any rescue mission speed also is of the utmost importance. This is why we must explore heuristics that make the processing of the collected data faster. The result of this processing must be dependable and must significantly enhance the success of the rescue mission. This work proposes such a heuristic. The results obtained from this heuristic is compared with the results obtained from a process that best mimics an ad-hoc retrieval. Keeping in mind that human ingenuity can never be replaced, in this thesis we create a heuristic that will render a reliable plan of action yielding more predictable results in a disaster recovery situation. Here optimum retrieval means an act of recovery or restoration from any terrain in the most efficient way. Such a process of recovery is very useful when faced with a disaster scenario such as a hurricane or a manmade calamity on a large scale.
Library of Congress Subject Headings
Evacuation of civilians--Computer simulation; Disaster relief--Computer simulation; Heuristic
Department, Program, or Center
Computer Engineering (KGCOE)
Murthy, Sapna Guniguntla, "Disaster recovery heuristic" (2009). Thesis. Rochester Institute of Technology. Accessed from
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