Efficient computation of evacuation routes on a three-dimensional geometric network

•We define a real-time emergency evacuation problem that seeks for rapid evacuation routes in buildings.•We formulate the stochastic routing problem as a non-linear routing problem subject to node-wise constraints.•We prove the problem to be NP-hard.•We suggest the exact dynamic programming algorith...

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Veröffentlicht in:Computers & industrial engineering Jg. 76; S. 231 - 242
Hauptverfasser: Tang, Huajun, Elalouf, Amir, Levner, Eugene, Cheng, T.C.E.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Ltd 01.10.2014
Pergamon Press Inc
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ISSN:0360-8352, 1879-0550
Online-Zugang:Volltext
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Zusammenfassung:•We define a real-time emergency evacuation problem that seeks for rapid evacuation routes in buildings.•We formulate the stochastic routing problem as a non-linear routing problem subject to node-wise constraints.•We prove the problem to be NP-hard.•We suggest the exact dynamic programming algorithm and two polynomial time approximation algorithms.•We present and discuss a case study and results of computational experiments. We consider a real-time emergency evacuation problem that seeks to compute a set of rapid evacuation routes in a building. Given a three-dimensional geometric structure of the evacuation network, an emergency evacuation route is a sequence of movements of people away from the threat or actual occurrence of a hazard (such as a fire, a hidden bomb) to a safe exit in the network. In such a network each room/crossing/exit in the building is designated as a node and the corridors/staircases/links between the rooms are edges. The evacuation times assigned to the edges are normally distributed random variables. This stochastic routing problem subject to deadline constraints is NP-hard. We provide a new pseudo-polynomial-time dynamic programming algorithm to solve this problem. Based on this algorithm, we construct two types of approximation algorithm, namely a fully polynomial-time approximation scheme providing “almost-optimal” solutions and a fully polynomial-time approximately feasible scheme yielding a best “almost feasible” solution. We present a case study and results of computational experiments to illustrate the working and efficacy of the proposed solution methods, respectively.
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ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2014.08.003