Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

Yongjian Du; Jinhua Sun; Qianglin Duan; Kaixuan Qi; Huahua Xiao; Kim Meow Liew

doi:10.1016/j.jlp.2020.104148

Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

Yongjian Du, Jinhua Sun^*, Qianglin Duan, Kaixuan Qi, Huahua Xiao^*, Kim Meow Liew

^*Corresponding author for this work

Department of Architecture and Civil Engineering

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

30 Citations (Scopus)

Abstract

Accidents in chemical industrial parks can result in mass casualties and the risk usually escalates due to domino effects. However, most of the existing models of emergency logistics do not account for domino effect and may be unsuitable for emergency response to accidents in chemical industrial parks. This paper presents a mathematical model proposed for optimal assignments of allocating and scheduling emergency resources for rescuing victims and preventing accident spreading simultaneously. The detailed characteristics of accident scenarios and emergency resources are taken into account. Based on this, the efficiency of emergency response is evaluated by the total number of fatalities and the amount of losses caused by domino effects which are the optimal objectives of the model. A numerical case study was conducted by solving the model using a designed heuristic algorithm. The results showed the applicability and reliability of the proposed model for making optimal assignments for emergency response to accidents in chemical industrial parks.

Original language	English
Article number	104148
Pages (from-to)	1-12
Number of pages	12
Journal	Journal of Loss Prevention in the Process Industries
Volume	65
Online published	27 Apr 2020
DOIs	https://doi.org/10.1016/j.jlp.2020.104148
Publication status	Published - May 2020

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Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

Chemical industrial park
Domino effect
Emergency response
Mathematical model

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10.1016/j.jlp.2020.104148

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@article{5e2fe381849f477680b465231528ac5a,

title = "Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks",

abstract = "Accidents in chemical industrial parks can result in mass casualties and the risk usually escalates due to domino effects. However, most of the existing models of emergency logistics do not account for domino effect and may be unsuitable for emergency response to accidents in chemical industrial parks. This paper presents a mathematical model proposed for optimal assignments of allocating and scheduling emergency resources for rescuing victims and preventing accident spreading simultaneously. The detailed characteristics of accident scenarios and emergency resources are taken into account. Based on this, the efficiency of emergency response is evaluated by the total number of fatalities and the amount of losses caused by domino effects which are the optimal objectives of the model. A numerical case study was conducted by solving the model using a designed heuristic algorithm. The results showed the applicability and reliability of the proposed model for making optimal assignments for emergency response to accidents in chemical industrial parks.",

keywords = "Chemical industrial park, Domino effect, Emergency response, Mathematical model",

author = "Yongjian Du and Jinhua Sun and Qianglin Duan and Kaixuan Qi and Huahua Xiao and Liew, {Kim Meow}",

note = "Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).",

year = "2020",

month = may,

doi = "10.1016/j.jlp.2020.104148",

language = "English",

volume = "65",

pages = "1--12",

journal = "Journal of Loss Prevention in the Process Industries",

issn = "0950-4230",

publisher = "Elsevier B.V.",

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TY - JOUR

T1 - Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

AU - Du, Yongjian

AU - Sun, Jinhua

AU - Duan, Qianglin

AU - Qi, Kaixuan

AU - Xiao, Huahua

AU - Liew, Kim Meow

N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

PY - 2020/5

Y1 - 2020/5

N2 - Accidents in chemical industrial parks can result in mass casualties and the risk usually escalates due to domino effects. However, most of the existing models of emergency logistics do not account for domino effect and may be unsuitable for emergency response to accidents in chemical industrial parks. This paper presents a mathematical model proposed for optimal assignments of allocating and scheduling emergency resources for rescuing victims and preventing accident spreading simultaneously. The detailed characteristics of accident scenarios and emergency resources are taken into account. Based on this, the efficiency of emergency response is evaluated by the total number of fatalities and the amount of losses caused by domino effects which are the optimal objectives of the model. A numerical case study was conducted by solving the model using a designed heuristic algorithm. The results showed the applicability and reliability of the proposed model for making optimal assignments for emergency response to accidents in chemical industrial parks.

AB - Accidents in chemical industrial parks can result in mass casualties and the risk usually escalates due to domino effects. However, most of the existing models of emergency logistics do not account for domino effect and may be unsuitable for emergency response to accidents in chemical industrial parks. This paper presents a mathematical model proposed for optimal assignments of allocating and scheduling emergency resources for rescuing victims and preventing accident spreading simultaneously. The detailed characteristics of accident scenarios and emergency resources are taken into account. Based on this, the efficiency of emergency response is evaluated by the total number of fatalities and the amount of losses caused by domino effects which are the optimal objectives of the model. A numerical case study was conducted by solving the model using a designed heuristic algorithm. The results showed the applicability and reliability of the proposed model for making optimal assignments for emergency response to accidents in chemical industrial parks.

KW - Chemical industrial park

KW - Domino effect

KW - Emergency response

KW - Mathematical model

UR - http://www.scopus.com/inward/record.url?scp=85084251567&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85084251567&origin=recordpage

U2 - 10.1016/j.jlp.2020.104148

DO - 10.1016/j.jlp.2020.104148

M3 - RGC 21 - Publication in refereed journal

SN - 0950-4230

VL - 65

SP - 1

EP - 12

JO - Journal of Loss Prevention in the Process Industries

JF - Journal of Loss Prevention in the Process Industries

M1 - 104148

ER -

Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

Abstract

Bibliographical note

Research Keywords

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GRF: Investigation of the Fire Performance of Double-skin Glass Facades

Making Emergency Decision Based on Fuzzy and Uncertain Multiple Attribute Decision

Cite this

Optimal Assignments of Allocating and Scheduling Emergency Resources to Accidents in Chemical Industrial Parks

Abstract

Bibliographical note

Research Keywords

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Projects

GRF: Investigation of the Fire Performance of Double-skin Glass Facades

Student theses

Making Emergency Decision Based on Fuzzy and Uncertain Multiple Attribute Decision

Cite this