Skip to main content
Kent Academic Repository

A Scenario Planning Approach for Shelter Location and Evacuation Routing

Esposito Amideo, Annunziata and Scaparra, Maria Paola (2017) A Scenario Planning Approach for Shelter Location and Evacuation Routing. In: Sforza, Antonio and Sterle, Claudio, eds. Optimization and Decision Science: Methodologies and Applications. Springer Proceedings in Mathematics & Statistics, 217 . Springer, pp. 567-576. ISBN 978-3-319-67307-3. E-ISBN 978-3-319-67308-0. (doi:10.1007/978-3-319-67308-0_57) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:64448)

PDF Author's Accepted Manuscript
Language: English

Restricted to Repository staff only
Contact us about this Publication
[thumbnail of A Scenario Planning Approach for Shelter Location and Evacuation Routing.pdf]
Official URL:


Emergency planning operations are one of the key aspects of Disaster Operations Management (DOM) [1]. This work presents a scenario-based location-allocation-routing model to optimise evacuation planning decisions, including where to establish shelter sites and which routes to arrange to reach them, across different network disruption scenarios. The model considers both supported-evacuation and self-evacuation. The objective is to minimise the duration of the supported-evacuation while guaranteeing that the routes of self-evacuees do not exceed a given travelling time threshold. Both shelter location and routing decisions are optimised so as to identify solutions which perform well across different disruption scenarios. A mathematical formulation of this model is provided, which can be solved through a general-purpose solver optimisation package for modest size instances. Some computational results are reported.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-319-67308-0_57
Uncontrolled keywords: Disaster management, Evacuation planning, Shelter location
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Paola Scaparra
Date Deposited: 15 Nov 2017 15:20 UTC
Last Modified: 19 Sep 2023 15:03 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Esposito Amideo, Annunziata.

Creator's ORCID:
CReDIT Contributor Roles:

Scaparra, Maria Paola.

Creator's ORCID:
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.