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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 54472 (09)
- University: Sharif University of Technology
- Department: Civil Engineering
- Advisor(s): Poorzahedy, Hossein
- Abstract:
- Throughout history, natural and unnatural disasters have caused great financial and human losses to human beings. Although these incidents are sometimes unpredictable and inevitable, with proper management, the casualties can be reduced. To optimally manage disaster response operations, it is essential to understand people’s vehicular movements in chaotic situations. This can be achieved by examining previous earthquakes. In the post-earthquake conditions, as the network experiences sudden and heavy loading, not only the debris falling on the roads but also the traffic congestion caused by the scared people will cause the links to close, and this will disrupt the relief and rescue operations. In addition, the lack of knowledge of disaster management forces about the post-disaster situation leads to a decrease in the efficiency of relief and rescue operations. The purpose of this study is to first identify the real-time travel demand in the aftermath of an earthquake in an urban area and then to answer this question: "Following an arbitrary earthquake in a vulnerable urban transportation network, considering the uncertainties related to reduced supply and increased demand, how should be the closed links’ reopening program to maximize the number of people rescued from the rubble?" In this study, using the ant algorithm, a method to achieve the link reopening program, which in 99% of cases gives an acceptable answer, is presented. The results showed that in order to increase efficiency, priority should be given to reopening links that provide access to the affected areas in the shortest possible time. In addition, the importance of locating aid teams was emphasized. It was also observed in the experimental network that full knowledge of disaster management forces about the failures can lead to an improvement of at least 12.5% in the performance of the assistance system
- Keywords:
- Earthquake ; Disaster Management ; Relief Operations ; Roads Reopening ; Ant Colony Algorithm ; Travel Demand Estimation
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