Dr John Fry J.M.Fry@hull.ac.uk
Senior Lecturer in Applied Mathematics
Quantitative decision-making for the next generation of smarter evacuations
Fry, John; Galla, Tobias; Binner, Jane
Authors
Tobias Galla
Jane Binner
Contributors
John Preston
Editor
Jane M Binner
Editor
Layla Branicki
Editor
Tobias Galla
Editor
Nick Jones
Editor
James King
Editor
Magdalini Kolokitha
Editor
Michalis Smyrnakis
Editor
Abstract
In this chapter we discuss the mathematical modelling of the next generation of smarter evacuations. Alongside a burgeoning literature on resilience we formulate a quantitative decision-making framework through which Social Media can be used to deliver more efficient evacuations. Our approach is flexible and improves upon existing models by allowing incoming information to be incorporated sequentially. Further, our model is the first of its kind to consider the effects of information quality (including abuse) and over-crowding upon network systems. In a high-quality information regime the potential benefits of Social Media increase as the size of the potential delays increases. Simulation results show that by not using updated information, as proposed in this study, final evacuation times are increased by 20 % and in some cases can be more than doubled. In a low-quality regime Social Media provides noisy information and other alternatives—including random allocation strategies and peer-to-peer communication—may be more effective.
Citation
Fry, J., Galla, T., & Binner, J. (2014). Quantitative decision-making for the next generation of smarter evacuations. In J. Preston, J. M. Binner, L. Branicki, T. Galla, N. Jones, J. King, M. Kolokitha, & M. Smyrnakis (Eds.), City Evacuations: An Interdisciplinary Approach (63-87). Springer. https://doi.org/10.1007/978-3-662-43877-0_4
Online Publication Date | Aug 2, 2014 |
---|---|
Publication Date | 2014 |
Deposit Date | Feb 4, 2022 |
Publisher | Springer |
Pages | 63-87 |
Book Title | City Evacuations: An Interdisciplinary Approach |
ISBN | 9783662438763; 9783662512364 |
DOI | https://doi.org/10.1007/978-3-662-43877-0_4 |
Public URL | https://hull-repository.worktribe.com/output/3920963 |
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