Browsing by Subject "Disasters"

Now showing 1 - 3 of 3

Open Access
3-Boyutlu orman yangını yayılımı sistemi
(IEEE, 2008) Köse, Kıvanç; Yılmaz, E.; Grammalidis, N.; Aktuğ, B.; Çetin, A. Enis; Aydın, İ.
In the last few years, due to the global warming and draught related to it, there is an increase in the number of forest fires. Forest fire detection is mainly done by people but there exists some automated systems in this field too. Besides the detection of the forest fires, effective fire extinhguising has an important role in fire fighting. If the spread of the fire can be predicted from the starting, early intervene can be achieved and fire can be extinguished swiftly. Using the Fire Propagation Simulator explained here it is aimed, to predict the fire development beforehand and to visulalize this predictions on a 3D-GIS environment. ©2008 IEEE.
Open Access
Solution methodologies for debris removal in disaster response
(Springer, 2016) Berktaş, N.; Kara, B. Y.; Karaşan, O. E.
During the disaster response phase of the emergency relief, the aim is to reduce loss of human life by reaching disaster affected areas with relief items as soon as possible. Debris caused by the disaster blocks the roads and prevents emergency aid teams to access the disaster affected regions. Deciding which roads to clean to transport relief items is crucial to diminish the negative impact of a disaster on human health. Despite the significance of the problem during response phase, in the literature debris removal is mostly studied in the recovery or the reconstruction phases of a disaster. The aim of this study is providing solution methodologies for debris removal problem in the response phase in which effective and fast relief routing is of utmost importance. In particular, debris removal activities on certain blocked arcs have to be scheduled to reach a set of critical nodes such as schools and hospitals. To this end, two mathematical models are developed with different objectives. The first model aims to minimize the total time spent to reach all the critical nodes whereas the second minimizes the weighted sum of visiting times where weights indicate the priorities of critical nodes. Since obtaining solutions quickly is important in the early post-disaster, heuristic algorithms are also proposed. Two data sets belonging to Kartal and Bakırköy districts of İstanbul are used to test the mathematical models and heuristics.
Open Access
Supporting hurricane inventory management decisions with consumer demand estimates
(Elsevier B.V., 2016) Morrice, D. J.; Cronin, P.; Tanrisever, F.; Butler, J. C.
Matching supply and demand can be very challenging for anyone attempting to provide goods or services during the threat of a natural disaster. In this paper, we consider inventory allocation issues faced by a retailer during a hurricane event and provide insights that can be applied to humanitarian operations during slow-onset events. We start with an empirical analysis using regression that triangulates three sources of information: a large point-of-sales data set from a Texas Gulf Coast retailer, the retailer's operational and logistical constraints, and hurricane forecast data from the National Hurricane Center (NHC). We establish a strong association between the timing of the hurricane weather forecast, the forecasted landfall position of the storm, and hurricane sales. Storm intensity is found to have a weaker association on overall inventory decisions. Using the results of the empirical analysis and the NHC forecast data, we construct a state-space model of demand during the threat of a hurricane and develop an inventory management model to satisfy consumer demand prior to a hurricane making landfall. Based on the structure of the problem, we model this situation as a two-stage, two-location inventory allocation model from a centralized distribution center that balances transportation, shortage and holding costs. The model is used to explore the role of recourse, i.e., deferring part of the inventory allocation until observing the state of the hurricane as it moves towards landfall. Our approach provides valuable insights into the circumstances under which recourse may or may not be worthwhile in any setting where an anticipated extreme event drives consumer demand.