A multi-objective stochastic programming model for post-disaster management

This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use of emergency resources. For this purpose, a stochastic mixed-integer programming model is provided to formulate the problem. The objective fun...

Full description

Saved in:
Bibliographic Details
Published in:Transportmetrica (Abingdon, Oxfordshire, UK) Vol. 18; no. 3; pp. 1103 - 1126
Main Authors: Gharib, Mehrdad, Fatemi Ghomi, Seyyed Mohammad Taghi, Jolai, Fariborz
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 02.12.2022
Taylor & Francis Ltd
Subjects:
Algorithms
Casualties
Completion time
Disaster management
Earthquakes
Emergency medical services
Emergency procedures
Genetic algorithms
Heuristic methods
Integer programming
Mathematical analysis
Mathematical programming
Mixed integer
multi-objective
multi-objective simulated annealing
non-dominated sorting genetic algorithm
Simulated annealing
Sorting algorithms
Stochastic models
Stochastic programming
ϵ-constraint method
Iran
ISSN:2324-9935, 2324-9943
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use of emergency resources. For this purpose, a stochastic mixed-integer programming model is provided to formulate the problem. The objective functions of the model are (1) maximizing the survival probability of patients, (2) minimizing the maximum of completion time of treatment of all patients, and (3) minimizing the total cost of operations. The model is solved with the ϵ-constraint method. Due to the NP-hardness of the problem which is a significant challenge in the literature, two innovative meta-heuristic algorithms are proposed, i.e. a non-dominated sorting genetic algorithm (NSGA-II) and a multi-objective simulated annealing (MOSA). Finally, a comprehensive computational analysis is performed for evaluation purposes. Also, a case study is made on the earthquake in Iran, which illustrates the real-world application of the model. Highlights A stochastic multi-objective mathematical programming model to allocate patients to hospitals and treat them. NSGA-II and MOSA are proposed, in addition to ϵ-constraint method as solution methods. Performance of two meta-heuristic algorithms is measured with five evaluation metrics. The study showed that NSGA-II is more effective than MOSA. The model was implemented on a real-world case, Tabriz earthquake in Iran.
AbstractList This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use of emergency resources. For this purpose, a stochastic mixed-integer programming model is provided to formulate the problem. The objective functions of the model are (1) maximizing the survival probability of patients, (2) minimizing the maximum of completion time of treatment of all patients, and (3) minimizing the total cost of operations. The model is solved with the ϵ-constraint method. Due to the NP-hardness of the problem which is a significant challenge in the literature, two innovative meta-heuristic algorithms are proposed, i.e. a non-dominated sorting genetic algorithm (NSGA-II) and a multi-objective simulated annealing (MOSA). Finally, a comprehensive computational analysis is performed for evaluation purposes. Also, a case study is made on the earthquake in Iran, which illustrates the real-world application of the model.HighlightsA stochastic multi-objective mathematical programming model to allocate patients to hospitals and treat them.NSGA-II and MOSA are proposed, in addition to ϵ-constraint method as solution methods.Performance of two meta-heuristic algorithms is measured with five evaluation metrics.The study showed that NSGA-II is more effective than MOSA.The model was implemented on a real-world case, Tabriz earthquake in Iran.
This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use of emergency resources. For this purpose, a stochastic mixed-integer programming model is provided to formulate the problem. The objective functions of the model are (1) maximizing the survival probability of patients, (2) minimizing the maximum of completion time of treatment of all patients, and (3) minimizing the total cost of operations. The model is solved with the ϵ-constraint method. Due to the NP-hardness of the problem which is a significant challenge in the literature, two innovative meta-heuristic algorithms are proposed, i.e. a non-dominated sorting genetic algorithm (NSGA-II) and a multi-objective simulated annealing (MOSA). Finally, a comprehensive computational analysis is performed for evaluation purposes. Also, a case study is made on the earthquake in Iran, which illustrates the real-world application of the model. Highlights A stochastic multi-objective mathematical programming model to allocate patients to hospitals and treat them. NSGA-II and MOSA are proposed, in addition to ϵ-constraint method as solution methods. Performance of two meta-heuristic algorithms is measured with five evaluation metrics. The study showed that NSGA-II is more effective than MOSA. The model was implemented on a real-world case, Tabriz earthquake in Iran.
Author Gharib, Mehrdad
Fatemi Ghomi, Seyyed Mohammad Taghi
Jolai, Fariborz
Author_xml – sequence: 1
  givenname: Mehrdad
  surname: Gharib
  fullname: Gharib, Mehrdad
  organization: Amirkabir University of Technology
– sequence: 2
  givenname: Seyyed Mohammad Taghi
  orcidid: 0000-0003-4363-994X
  surname: Fatemi Ghomi
  fullname: Fatemi Ghomi, Seyyed Mohammad Taghi
  email: fatemi@aut.ac.ir
  organization: Amirkabir University of Technology
– sequence: 3
  givenname: Fariborz
  orcidid: 0000-0003-0824-8513
  surname: Jolai
  fullname: Jolai, Fariborz
  organization: University of Tehran
BookMark eNqFkE1LAzEQhoMoWGt_grDgeWs-NrsJXizFLyx40XPI7iY1ZZPUJFX6701p9eBB5zLD8L7vDM8ZOHbeKQAuEJwiyOAVJrjinNAphhhNEces4fAIjHb7kvOKHP_MhJ6CSYwrmIuhmiM2Ak-zwm6GZErfrlSXzIcqYvLdm4zJdMU6-GWQ1hq3LKzv1VBoH4q1j6nsTcwaFQornVwqq1w6BydaDlFNDn0MXu9uX-YP5eL5_nE-W5QdISyVFLe0aTRlbdNARhViLeWIM9T3Sld55qpqMZdUykYpSBUjpIYatoxSWktNxuByn5vfe9-omMTKb4LLJwVuKlYTlFFk1fVe1QUfY1BadCbJZLxLQZpBICh2AMU3QLEDKA4As5v-cq-DsTJs__Xd7H3GZVRWfvow9CLJ7eCDDtJ1Jgryd8QX9eCJBw
CitedBy_id crossref_primary_10_1080_23249935_2023_2299684
crossref_primary_10_1080_23249935_2022_2103205
crossref_primary_10_1186_s12911_022_02074_3
crossref_primary_10_1007_s13198_021_01488_y
Cites_doi 10.1016/S0360-8352(01)00059-6
10.1080/23249935.2018.1477852
10.1057/jors.2010.5
10.1016/j.ejor.2018.02.022
10.1016/j.omega.2016.02.006
10.1109/TSMC.1971.4308298
10.1016/j.ejor.2016.05.047
10.1016/j.cie.2019.02.003
10.1016/j.ijpe.2009.10.004
10.1016/j.eswa.2017.01.050
10.1007/s10729-017-9409-3
10.1002/(SICI)1099-1360(199907)8:4<221::AID-MCDA247>3.0.CO;2-O
10.1016/j.tre.2016.12.011
10.1080/24725854.2020.1727069
10.1016/j.ejor.2016.04.041
10.1016/j.omega.2017.08.001
10.1016/j.tre.2012.09.001
10.1016/j.ejor.2016.01.028
10.1080/23249935.2020.1725179
10.1007/s10729-014-9280-4
10.1057/jors.2012.72
10.1007/s10729-015-9332-4
10.1057/jors.2010.145
10.1016/j.apm.2017.10.041
10.1016/j.amc.2009.03.037
10.1016/j.ejor.2017.11.058
10.1016/j.apm.2013.07.028
10.1126/science.220.4598.671
10.1016/j.eswa.2019.01.042
10.1016/j.apm.2015.12.013
10.1109/4235.996017
10.1016/j.orhc.2015.06.006
10.1007/s00024-017-1617-8
10.1002/hec.2851
10.1016/j.jclepro.2017.11.037
ContentType Journal Article
Copyright 2021 Hong Kong Society for Transportation Studies Limited 2021
2021 Hong Kong Society for Transportation Studies Limited
Copyright_xml – notice: 2021 Hong Kong Society for Transportation Studies Limited 2021
– notice: 2021 Hong Kong Society for Transportation Studies Limited
DBID AAYXX
CITATION
8FD
FR3
KR7
DOI 10.1080/23249935.2021.1928790
DatabaseName CrossRef
Technology Research Database
Engineering Research Database
Civil Engineering Abstracts
DatabaseTitle CrossRef
Technology Research Database
Civil Engineering Abstracts
Engineering Research Database
DatabaseTitleList Technology Research Database
DeliveryMethod fulltext_linktorsrc
Discipline Economics
EISSN 2324-9943
EndPage 1126
ExternalDocumentID 10_1080_23249935_2021_1928790
1928790
Genre Research Article
GeographicLocations Iran
GeographicLocations_xml – name: Iran
GroupedDBID .QJ
0BK
0R~
30N
AAENE
AAGDL
AAHIA
AAJMT
AALDU
AAMIU
AAPUL
AAQRR
ABFIM
ABLIJ
ABPAQ
ABPEM
ABXUL
ABXYU
ACIWK
ACTIO
ADCVX
ADGTB
AEOZL
AFRVT
AGDLA
AGMYJ
AIJEM
AKBVH
AKOOK
ALMA_UNASSIGNED_HOLDINGS
ALQZU
AQRUH
AQTUD
AVBZW
BLEHA
CCCUG
DGEBU
DKSSO
E~A
E~B
H13
IPNFZ
KYCEM
LJTGL
M4Z
RIG
RNANH
ROSJB
RTWRZ
S-T
SNACF
TASJS
TBQAZ
TDBHL
TEN
TFL
TFT
TFW
TTHFI
TUROJ
UT5
UU3
ZGOLN
~S~
AAYXX
CITATION
8FD
FR3
KR7
ID FETCH-LOGICAL-c338t-52b577f58b77085e18b591981ddef4b599e4b29a5aa7ee05e83360f0b85556af3
IEDL.DBID TFW
ISICitedReferencesCount 8
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000658226100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 2324-9935
IngestDate Wed Aug 13 03:31:11 EDT 2025
Sat Nov 29 01:33:23 EST 2025
Tue Nov 18 20:43:03 EST 2025
Mon Oct 20 23:47:25 EDT 2025
IsPeerReviewed true
IsScholarly true
Issue 3
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c338t-52b577f58b77085e18b591981ddef4b599e4b29a5aa7ee05e83360f0b85556af3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-4363-994X
0000-0003-0824-8513
PQID 2748631021
PQPubID 2030011
PageCount 24
ParticipantIDs crossref_citationtrail_10_1080_23249935_2021_1928790
proquest_journals_2748631021
informaworld_taylorfrancis_310_1080_23249935_2021_1928790
crossref_primary_10_1080_23249935_2021_1928790
PublicationCentury 2000
PublicationDate 2022-12-02
PublicationDateYYYYMMDD 2022-12-02
PublicationDate_xml – month: 12
  year: 2022
  text: 2022-12-02
  day: 02
PublicationDecade 2020
PublicationPlace Abingdon
PublicationPlace_xml – name: Abingdon
PublicationTitle Transportmetrica (Abingdon, Oxfordshire, UK)
PublicationYear 2022
Publisher Taylor & Francis
Taylor & Francis Ltd
Publisher_xml – name: Taylor & Francis
– name: Taylor & Francis Ltd
References CIT0030
CIT0010
CIT0032
CIT0012
CIT0034
CIT0011
Taguchi G. (CIT0031) 1986
CIT0033
CIT0014
CIT0036
CIT0013
CIT0035
CIT0016
CIT0015
CIT0037
CIT0018
CIT0017
CIT0019
CIT0021
CIT0020
CIT0001
CIT0023
CIT0022
CIT0003
CIT0025
CIT0002
CIT0024
CIT0005
CIT0027
CIT0004
CIT0026
CIT0007
CIT0029
CIT0006
CIT0028
CIT0009
CIT0008
References_xml – ident: CIT0019
  doi: 10.1016/S0360-8352(01)00059-6
– ident: CIT0027
  doi: 10.1080/23249935.2018.1477852
– ident: CIT0003
  doi: 10.1057/jors.2010.5
– ident: CIT0021
  doi: 10.1016/j.ejor.2018.02.022
– ident: CIT0025
  doi: 10.1016/j.omega.2016.02.006
– ident: CIT0010
  doi: 10.1109/TSMC.1971.4308298
– ident: CIT0026
  doi: 10.1016/j.ejor.2016.05.047
– ident: CIT0036
  doi: 10.1016/j.cie.2019.02.003
– ident: CIT0020
  doi: 10.1016/j.ijpe.2009.10.004
– ident: CIT0004
  doi: 10.1016/j.eswa.2017.01.050
– ident: CIT0034
  doi: 10.1007/s10729-017-9409-3
– ident: CIT0032
  doi: 10.1002/(SICI)1099-1360(199907)8:4<221::AID-MCDA247>3.0.CO;2-O
– ident: CIT0037
  doi: 10.1016/j.tre.2016.12.011
– ident: CIT0029
  doi: 10.1080/24725854.2020.1727069
– ident: CIT0001
  doi: 10.1016/j.ejor.2016.04.041
– ident: CIT0007
  doi: 10.1016/j.omega.2017.08.001
– ident: CIT0022
  doi: 10.1016/j.tre.2012.09.001
– ident: CIT0030
  doi: 10.1016/j.ejor.2016.01.028
– ident: CIT0008
  doi: 10.1080/23249935.2020.1725179
– ident: CIT0024
  doi: 10.1007/s10729-014-9280-4
– ident: CIT0016
  doi: 10.1057/jors.2012.72
– ident: CIT0013
  doi: 10.1007/s10729-015-9332-4
– volume-title: Introduction to Quality Engineering: Designing Quality Into Products and Processes
  year: 1986
  ident: CIT0031
– ident: CIT0015
  doi: 10.1057/jors.2010.145
– ident: CIT0017
  doi: 10.1016/j.apm.2017.10.041
– ident: CIT0018
  doi: 10.1016/j.amc.2009.03.037
– ident: CIT0009
  doi: 10.1016/j.ejor.2017.11.058
– ident: CIT0035
  doi: 10.1016/j.apm.2013.07.028
– ident: CIT0014
  doi: 10.1126/science.220.4598.671
– ident: CIT0002
  doi: 10.1016/j.eswa.2019.01.042
– ident: CIT0011
  doi: 10.1016/j.apm.2015.12.013
– ident: CIT0006
  doi: 10.1109/4235.996017
– ident: CIT0023
  doi: 10.1016/j.orhc.2015.06.006
– ident: CIT0028
– ident: CIT0012
  doi: 10.1007/s00024-017-1617-8
– ident: CIT0033
  doi: 10.1002/hec.2851
– ident: CIT0005
  doi: 10.1016/j.jclepro.2017.11.037
SSID ssj0000816918
Score 2.307367
Snippet This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use...
SourceID proquest
crossref
informaworld
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 1103
SubjectTerms Algorithms
Casualties
Completion time
Disaster management
Earthquakes
Emergency medical services
Emergency procedures
Genetic algorithms
Heuristic methods
Integer programming
Mathematical analysis
Mathematical programming
Mixed integer
multi-objective
multi-objective simulated annealing
non-dominated sorting genetic algorithm
Simulated annealing
Sorting algorithms
Stochastic models
Stochastic programming
ϵ-constraint method
Title A multi-objective stochastic programming model for post-disaster management
URI https://www.tandfonline.com/doi/abs/10.1080/23249935.2021.1928790
https://www.proquest.com/docview/2748631021
Volume 18
WOSCitedRecordID wos000658226100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAWR
  databaseName: Taylor and Francis Online Journals
  customDbUrl:
  eissn: 2324-9943
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000816918
  issn: 2324-9935
  databaseCode: TFW
  dateStart: 20130101
  isFulltext: true
  titleUrlDefault: https://www.tandfonline.com
  providerName: Taylor & Francis
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3LSgMxFA1SBN34FqtVsnA7dR7JJFkWsQhCcVGxuyGZJFixDzqj329uJlMUkS50N5s7hJvHPSecnIvQNU3y1DKu3AwoGxGZ6khpmUekZEyXuYkJ0b7ZBBuN-GQiHoOasAqySuDQtjGK8Gc1bG6pqlYRdwMgwJVV6thdmvQdROFMAGt3yB5EfePh8_qWBdpKCH_JB0ERRLXPeH770bcC9c2-9Mdx7WvQcP8fRn-A9gIAxYNmxRyiLTM_Qjvt--TqGD0MsFcZRgv12pyG2AHE8kWCozMOeq6Zq3jYd9HBbuR4uajqSE8rCbYLeLaW1Jygp-Hd-PY-Ci0XotJx1drRUkUZs5QrxhwYMwlXVCTCgVptLHHfwhCVCkmlZMbE1PAsy2MbK04pzaXNTlFnvpibM4R1KuIyyQ3JmCVSSwVee0C_YpaXNmNdRNo8F2XwI4e2GG9FEmxL20wVkKkiZKqL-uuwZWPIsSlAfJ3EovY3IbZpW1JkG2J77YwXYW9XhePxPM-gJfr5H359gXZTeEkBypi0hzr16t1cou3yo55Wqyu_ij8B_8vryg
linkProvider Taylor & Francis
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LSwMxEA6iQr34FqtVc_C6dR_JZnMsYlFae6rYW0iyCVbsg-7q7zezj9Ii0oPe9jJLmDxmvmHm-xC6pUEcWpYotwPKekSGqadSGXtEM5bq2PiEpIXYBBsMktGIr87CQFslYGhbEkUUbzVcbihG1y1xd5AFuLhKHbwLg7bLURLGHWzfAXU6AGDD7uuyzgLCErwo84GVB2b1IM9vf1oLUWsEpj8e7CIKdQ_-Y_2HaL_KQXGnPDRHaMtMj1GjHlHOTlCvg4tGQ2-m3ssHEbscUb9JIHXGVUvXxAU9XAjpYLd0PJ9luZeOMwnMC3iy7Ko5RS_dh-H9o1epLnjawdXcIVNFGbM0UYy5fMwEiaI84C6vTY0l7psbokIuqZTMGJ-aJIpi3_oqoZTG0kZnaHs6m5pzhNOQ-zqIDYmYJTKVCuj2AIH5LNY2Yk1EakcLXVGSgzLGhwgq5tLaUwI8JSpPNVF7aTYvOTk2GfDVXRR5UQyxpXKJiDbYtuotF9X1zoSD8kkcgSr6xR9-fYMaj8Pnvug_DXqXaC-EwQpolAlbaDtffJortKu_8nG2uC6O9Dfufe_t
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3LSgMxFA2iom58i9WqWbhNnUcymSyLWpRK6aJidyGZJFixDzqj328ykykWkS50N5s7hJvHPSfcnAPANQmTyNBU2hmQBmERKSSVSBDOKFVZogOMVWk2QXu9dDhkfd9NmPu2SsehTSUUUZ7VbnPPlKk74m4cCLBllVh2F4UtC1FSyixr37DQmbiFPei8LK5ZnK8EK2_5XBRyYfU7nt_-tFShlvRLf5zXZRHq7P3D8PfBrkegsF0tmQOwpieHYLt-oJwfgW4blm2GaCrfquMQWoSYvQon6Qx9Q9fYljxY2uhAO3I4m-YFUqNcON0FOF701ByD58794PYBec8FlFmyWlheKgmlhqSSUovGdJhKwkJmUa3SBttvprGMmCBCUK0DotM4TgITyJQQkggTn4D1yXSiTwFUEQuyMNE4pgYLJaQT23P8K6BJZmLaALjOM8-8ILnzxXjnodctrTPFXaa4z1QDtBZhs0qRY1UA-z6JvCivQkzlW8LjFbHNesa539w5t0Q-TWLniX72h19fga3-XYc_Pfa652Ancq8qXJdM1ATrxfxDX4DN7LMY5fPLckF_ARyW7p8
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+multi-objective+stochastic+programming+model+for+post-disaster+management&rft.jtitle=Transportmetrica+%28Abingdon%2C+Oxfordshire%2C+UK%29&rft.au=Gharib%2C+Mehrdad&rft.au=Fatemi+Ghomi%2C+Seyyed+Mohammad+Taghi&rft.au=Jolai%2C+Fariborz&rft.date=2022-12-02&rft.issn=2324-9935&rft.eissn=2324-9943&rft.volume=18&rft.issue=3&rft.spage=1103&rft.epage=1126&rft_id=info:doi/10.1080%2F23249935.2021.1928790&rft.externalDBID=n%2Fa&rft.externalDocID=10_1080_23249935_2021_1928790
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2324-9935&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2324-9935&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2324-9935&client=summon