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Dynamic emergency route planning for major chemical accidents: Models and application

Xu, Ke, Gai, Wen-mei, Salhi, Said (2020) Dynamic emergency route planning for major chemical accidents: Models and application. Safety Science, 135 . Article Number 105113. ISSN 0925-7535. (doi:10.1016/j.ssci.2020.105113) (KAR id:87783)

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Official URL
https://doi.org/10.1016/j.ssci.2020.105113

Abstract

Combining scenario construction with the characteristics of individual emergencybehavior is necessary for the emergency route planning of major chemical accidents. Weinvestigated this challenging decision problem and constructed a multi-indicator emergencyrisk assessment method that considers the evacuation speed of different population types andhealth consequences caused by various risk components. We also designed a modified Dijkstraalgorithm to solve this dynamic multi-objective route planning problem. The comparativeexperiment results demonstrated that the proposed algorithm performs relatively better thanthe traditional Dijkstra algorithm. Finally, we performed extensive case studies where oursimulation results demonstrate that the proposed model provides reliable and practicalemergency route planning services for various personnel types under different accidentscenarios. Compared with the commonly used single-dimensional assessment method, thiscomprehensive and informative assessment of the emergency risks faced by the population indifferent regions could serve as a useful reference for the formulation and implementation ofemergency plans in case of major chemical accidents.

Item Type: Article
DOI/Identification number: 10.1016/j.ssci.2020.105113
Uncontrolled keywords: emergency route planning; dynamic optimization; the modified Dijkstra algorithm; major chemical accidents; emergency risk assessment.
Subjects: H Social Sciences > HD Industries. Land use. Labor
Divisions: Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Said Salhi
Date Deposited: 27 Apr 2021 12:49 UTC
Last Modified: 28 Apr 2021 08:08 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/87783 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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