What is it about?
This work presents an integrated, efficient and fair, strategic evacuation planning tool. It is efficient as to how fast the population at risk is evacuated and it is fair in terms of the distance of safe shelters evacuees are assigned to and the length of the routes that they have to take to reach the shelters. With the methodology proposed in this work, the capability to generate efficient evacuation plans for mass evacuations in real size road networks considering a large number of scenarios (up to 1000) representing the uncertainty in evacuation demand, disruption/degradation of road network and disruption of shelters is attained. The algorithms in the paper can solve such instances of the evacuation problem in moderate times. This, we achieve by using second order cone programming duality results in a Benders decomposition setting.
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Why is it important?
There has been a significant increase in the number of natural and man-made disasters over the past decades. The massive amount of destruction caused and the tremendous operational challenges imposed by disasters on the governments and the humanitarian agencies, illustrate the importance of a disaster management program. An important part of such a program is to evacuate a disaster region to protect people threatened by the disaster. The unusual surge in traffic demand far beyond the capacity of the road network and the fact that people’s lives are at stake, make the evacuation traffic management problem critical. Often, the problem of locating safe shelters is solved independently from evacuation traffic management/planning problem or ignored. And generally evacuation traffic management/planning problem is solved with shelter location decisions as given. However, considering these two problems separately may result in suboptimal, i.e., less efficient evacuation plans. Considering these two problems simultaneously renders the problem a hard one. On top of all these, the uncertainty inherent in such problems increases the complexity of the problem. As such, saving human lives and the challenges of this problem are my main motivation.
Perspectives
I believe the most important result of this paper is to show the readers that a realistic, efficient, and fair evacuation plan can be achieved by the evacuation planning model and algorithms proposed. Although inclusion of congestion effects, shelter location decisions, and the incorporation of uncertainty represented by a large number of scenarios and using real size road networks render the evacuation planning problem a very hard one, the algorithms proposed in this paper solve the problem exactly and efficiently in moderate times. It is sad to see that necessary lessons are not taken after hurricanes such as Katrina and Rita to have better evacuation plans. As Houston Mayor said, “It takes a lot of preparation. You have to have an evacuation plan”. It takes time, effort, a lot of coordination but it is doable. In my opinion "evacuation without an evacuation plan" is a bad decision. I believe the methodology used in this paper can be used to prepare an efficient and fair, strategic evacuation plan that could help in mass evacuation of cities due to hurricanes such as Harvey and Irma or other kinds of disasters.
Vedat Bayram
TED University, Department of Industrial Engineering
Read the Original
This page is a summary of: Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach, Transportation Science, August 2017, INFORMS,
DOI: 10.1287/trsc.2017.0762.
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