Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model

Nowadays, according to the importance of sustainability objectives in supply chain (SC) design and planning, in addition to the economic objective, the social, environmental, and customer-oriented considerations play a vital role in the SCs' performance. On the other hand, SC resilience will ca...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Environment, development and sustainability development and sustainability, 2024-11, Vol.26 (11), p.27485-27527
Hauptverfasser: Safari, Lida, Sadjadi, Seyed Jafar, Sobhani, Farzad Movahedi
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 27527
container_issue 11
container_start_page 27485
container_title Environment, development and sustainability
container_volume 26
creator Safari, Lida
Sadjadi, Seyed Jafar
Sobhani, Farzad Movahedi
description Nowadays, according to the importance of sustainability objectives in supply chain (SC) design and planning, in addition to the economic objective, the social, environmental, and customer-oriented considerations play a vital role in the SCs' performance. On the other hand, SC resilience will cause sustainability to be less affected during disruption. This paper deals with the resilient sustainable supply chain design and planning (RSSCDP) problem under supply disruption risk. We developed a multi-objective robust model to solve the multi-product RSSCDP problem under various supply disruption scenarios. In this problem, the most important decisions related to SC designing and planning, such as facility location and determination of their capacities, supplier selection, inventory management, order allocation and transportation planning, lot sizing, and production planning, are taken into account. In the proposed model, four absorptive and adaptive resilience strategies are simultaneously applied, including (1) multiple sourcing, (2) backup supplier contracting, (3) raw material inventory pre-positioning, and (4) final product inventory pre-positioning. Also, a reasonable trading-off among four objectives, including economic, social, environmental, as well as customer-oriented objectives using the Lp-metric method, is made. In addition, a multi-objective robust scenario-based stochastic programming approach is employed to cope with the operational uncertainty of the parameters. Finally, some numerical studies of the RSSCDP problem are conducted to demonstrate the capabilities and effectiveness of the developed model. The results depict a 10 to 15 percent improvement in the objectives. The findings confirm that the proposed resilience strategies are efficient in mitigating supply disruptions and can maintain the SC sustainability under disruptions.
doi_str_mv 10.1007/s10668-023-03769-x
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3154160448</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3154160448</sourcerecordid><originalsourceid>FETCH-LOGICAL-c303t-22fc396b900aaae161f31eab07cf8bd258cd316046fa172803226d48ed2a489a3</originalsourceid><addsrcrecordid>eNp9kctKxDAUhosoOI6-gKuAGzfRXDppu5TBGwwIoutw2qRjxjapSSuOT-Ljms4oigtXOYTv-3PCnyTHlJxRQrLzQIkQOSaMY8IzUeC3nWRCZxnHrMhmu7_m_eQghBUhjBRMTJKPex1MY7TtEViFwhB6MBbKRse565o1qp7iBVIRW9oN0zVgrbFLNFil_TemTPBD1xtnkTfhGQ1hRAC1Q9Mb7MqVrnrzGlMrbcEbh0sIWiHvyvgkctFszTts_NYp3RwmezU0QR99ndPk8eryYX6DF3fXt_OLBa444T1mrK54IcqCEADQVNCaUw0lyao6LxWb5ZXiVJBU1EAzlhPOmFBprhWDNC-AT5PTbW7n3cugQy9bE3ds4ie1G4LkdJaOfppH9OQPunKDt3G7SDGWZxEdKbalKu9C8LqWnTct-LWkRI5lyW1ZMpYlN2XJtyjxrRQibJfa_0T_Y30CJuSb_A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3122871548</pqid></control><display><type>article</type><title>Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model</title><source>SpringerLink Journals</source><creator>Safari, Lida ; Sadjadi, Seyed Jafar ; Sobhani, Farzad Movahedi</creator><creatorcontrib>Safari, Lida ; Sadjadi, Seyed Jafar ; Sobhani, Farzad Movahedi</creatorcontrib><description>Nowadays, according to the importance of sustainability objectives in supply chain (SC) design and planning, in addition to the economic objective, the social, environmental, and customer-oriented considerations play a vital role in the SCs' performance. On the other hand, SC resilience will cause sustainability to be less affected during disruption. This paper deals with the resilient sustainable supply chain design and planning (RSSCDP) problem under supply disruption risk. We developed a multi-objective robust model to solve the multi-product RSSCDP problem under various supply disruption scenarios. In this problem, the most important decisions related to SC designing and planning, such as facility location and determination of their capacities, supplier selection, inventory management, order allocation and transportation planning, lot sizing, and production planning, are taken into account. In the proposed model, four absorptive and adaptive resilience strategies are simultaneously applied, including (1) multiple sourcing, (2) backup supplier contracting, (3) raw material inventory pre-positioning, and (4) final product inventory pre-positioning. Also, a reasonable trading-off among four objectives, including economic, social, environmental, as well as customer-oriented objectives using the Lp-metric method, is made. In addition, a multi-objective robust scenario-based stochastic programming approach is employed to cope with the operational uncertainty of the parameters. Finally, some numerical studies of the RSSCDP problem are conducted to demonstrate the capabilities and effectiveness of the developed model. The results depict a 10 to 15 percent improvement in the objectives. The findings confirm that the proposed resilience strategies are efficient in mitigating supply disruptions and can maintain the SC sustainability under disruptions.</description><identifier>ISSN: 1573-2975</identifier><identifier>ISSN: 1387-585X</identifier><identifier>EISSN: 1573-2975</identifier><identifier>DOI: 10.1007/s10668-023-03769-x</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Absorptivity ; Component and supplier management ; Customers ; Design ; Design optimization ; Disruption ; Earth and Environmental Science ; Ecology ; Economic Geology ; Economic Growth ; Economics ; Environment ; Environmental Economics ; Environmental Management ; inventories ; Inventory ; Inventory management ; Lot sizing ; Multiple objective analysis ; Optimization ; Optimization models ; Parameter robustness ; Parameter uncertainty ; Positioning ; Production planning ; Raw materials ; Resilience ; risk ; Robustness ; Stochastic programming ; Suppliers ; Supply ; supply chain ; Supply chain sustainability ; Supply chains ; Sustainability ; Sustainable Development ; transportation ; Transportation planning ; Uncertainty</subject><ispartof>Environment, development and sustainability, 2024-11, Vol.26 (11), p.27485-27527</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c303t-22fc396b900aaae161f31eab07cf8bd258cd316046fa172803226d48ed2a489a3</cites><orcidid>0000-0002-7677-0840 ; 0000-0002-7382-6351 ; 0000-0002-4602-2710</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10668-023-03769-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10668-023-03769-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Safari, Lida</creatorcontrib><creatorcontrib>Sadjadi, Seyed Jafar</creatorcontrib><creatorcontrib>Sobhani, Farzad Movahedi</creatorcontrib><title>Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model</title><title>Environment, development and sustainability</title><addtitle>Environ Dev Sustain</addtitle><description>Nowadays, according to the importance of sustainability objectives in supply chain (SC) design and planning, in addition to the economic objective, the social, environmental, and customer-oriented considerations play a vital role in the SCs' performance. On the other hand, SC resilience will cause sustainability to be less affected during disruption. This paper deals with the resilient sustainable supply chain design and planning (RSSCDP) problem under supply disruption risk. We developed a multi-objective robust model to solve the multi-product RSSCDP problem under various supply disruption scenarios. In this problem, the most important decisions related to SC designing and planning, such as facility location and determination of their capacities, supplier selection, inventory management, order allocation and transportation planning, lot sizing, and production planning, are taken into account. In the proposed model, four absorptive and adaptive resilience strategies are simultaneously applied, including (1) multiple sourcing, (2) backup supplier contracting, (3) raw material inventory pre-positioning, and (4) final product inventory pre-positioning. Also, a reasonable trading-off among four objectives, including economic, social, environmental, as well as customer-oriented objectives using the Lp-metric method, is made. In addition, a multi-objective robust scenario-based stochastic programming approach is employed to cope with the operational uncertainty of the parameters. Finally, some numerical studies of the RSSCDP problem are conducted to demonstrate the capabilities and effectiveness of the developed model. The results depict a 10 to 15 percent improvement in the objectives. The findings confirm that the proposed resilience strategies are efficient in mitigating supply disruptions and can maintain the SC sustainability under disruptions.</description><subject>Absorptivity</subject><subject>Component and supplier management</subject><subject>Customers</subject><subject>Design</subject><subject>Design optimization</subject><subject>Disruption</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Economic Geology</subject><subject>Economic Growth</subject><subject>Economics</subject><subject>Environment</subject><subject>Environmental Economics</subject><subject>Environmental Management</subject><subject>inventories</subject><subject>Inventory</subject><subject>Inventory management</subject><subject>Lot sizing</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>Parameter robustness</subject><subject>Parameter uncertainty</subject><subject>Positioning</subject><subject>Production planning</subject><subject>Raw materials</subject><subject>Resilience</subject><subject>risk</subject><subject>Robustness</subject><subject>Stochastic programming</subject><subject>Suppliers</subject><subject>Supply</subject><subject>supply chain</subject><subject>Supply chain sustainability</subject><subject>Supply chains</subject><subject>Sustainability</subject><subject>Sustainable Development</subject><subject>transportation</subject><subject>Transportation planning</subject><subject>Uncertainty</subject><issn>1573-2975</issn><issn>1387-585X</issn><issn>1573-2975</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kctKxDAUhosoOI6-gKuAGzfRXDppu5TBGwwIoutw2qRjxjapSSuOT-Ljms4oigtXOYTv-3PCnyTHlJxRQrLzQIkQOSaMY8IzUeC3nWRCZxnHrMhmu7_m_eQghBUhjBRMTJKPex1MY7TtEViFwhB6MBbKRse565o1qp7iBVIRW9oN0zVgrbFLNFil_TemTPBD1xtnkTfhGQ1hRAC1Q9Mb7MqVrnrzGlMrbcEbh0sIWiHvyvgkctFszTts_NYp3RwmezU0QR99ndPk8eryYX6DF3fXt_OLBa444T1mrK54IcqCEADQVNCaUw0lyao6LxWb5ZXiVJBU1EAzlhPOmFBprhWDNC-AT5PTbW7n3cugQy9bE3ds4ie1G4LkdJaOfppH9OQPunKDt3G7SDGWZxEdKbalKu9C8LqWnTct-LWkRI5lyW1ZMpYlN2XJtyjxrRQibJfa_0T_Y30CJuSb_A</recordid><startdate>20241101</startdate><enddate>20241101</enddate><creator>Safari, Lida</creator><creator>Sadjadi, Seyed Jafar</creator><creator>Sobhani, Farzad Movahedi</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>8BJ</scope><scope>8FD</scope><scope>C1K</scope><scope>FQK</scope><scope>FR3</scope><scope>JBE</scope><scope>KR7</scope><scope>SOI</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-7677-0840</orcidid><orcidid>https://orcid.org/0000-0002-7382-6351</orcidid><orcidid>https://orcid.org/0000-0002-4602-2710</orcidid></search><sort><creationdate>20241101</creationdate><title>Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model</title><author>Safari, Lida ; Sadjadi, Seyed Jafar ; Sobhani, Farzad Movahedi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c303t-22fc396b900aaae161f31eab07cf8bd258cd316046fa172803226d48ed2a489a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Absorptivity</topic><topic>Component and supplier management</topic><topic>Customers</topic><topic>Design</topic><topic>Design optimization</topic><topic>Disruption</topic><topic>Earth and Environmental Science</topic><topic>Ecology</topic><topic>Economic Geology</topic><topic>Economic Growth</topic><topic>Economics</topic><topic>Environment</topic><topic>Environmental Economics</topic><topic>Environmental Management</topic><topic>inventories</topic><topic>Inventory</topic><topic>Inventory management</topic><topic>Lot sizing</topic><topic>Multiple objective analysis</topic><topic>Optimization</topic><topic>Optimization models</topic><topic>Parameter robustness</topic><topic>Parameter uncertainty</topic><topic>Positioning</topic><topic>Production planning</topic><topic>Raw materials</topic><topic>Resilience</topic><topic>risk</topic><topic>Robustness</topic><topic>Stochastic programming</topic><topic>Suppliers</topic><topic>Supply</topic><topic>supply chain</topic><topic>Supply chain sustainability</topic><topic>Supply chains</topic><topic>Sustainability</topic><topic>Sustainable Development</topic><topic>transportation</topic><topic>Transportation planning</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Safari, Lida</creatorcontrib><creatorcontrib>Sadjadi, Seyed Jafar</creatorcontrib><creatorcontrib>Sobhani, Farzad Movahedi</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>International Bibliography of the Social Sciences</collection><collection>Engineering Research Database</collection><collection>International Bibliography of the Social Sciences</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environment, development and sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Safari, Lida</au><au>Sadjadi, Seyed Jafar</au><au>Sobhani, Farzad Movahedi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model</atitle><jtitle>Environment, development and sustainability</jtitle><stitle>Environ Dev Sustain</stitle><date>2024-11-01</date><risdate>2024</risdate><volume>26</volume><issue>11</issue><spage>27485</spage><epage>27527</epage><pages>27485-27527</pages><issn>1573-2975</issn><issn>1387-585X</issn><eissn>1573-2975</eissn><abstract>Nowadays, according to the importance of sustainability objectives in supply chain (SC) design and planning, in addition to the economic objective, the social, environmental, and customer-oriented considerations play a vital role in the SCs' performance. On the other hand, SC resilience will cause sustainability to be less affected during disruption. This paper deals with the resilient sustainable supply chain design and planning (RSSCDP) problem under supply disruption risk. We developed a multi-objective robust model to solve the multi-product RSSCDP problem under various supply disruption scenarios. In this problem, the most important decisions related to SC designing and planning, such as facility location and determination of their capacities, supplier selection, inventory management, order allocation and transportation planning, lot sizing, and production planning, are taken into account. In the proposed model, four absorptive and adaptive resilience strategies are simultaneously applied, including (1) multiple sourcing, (2) backup supplier contracting, (3) raw material inventory pre-positioning, and (4) final product inventory pre-positioning. Also, a reasonable trading-off among four objectives, including economic, social, environmental, as well as customer-oriented objectives using the Lp-metric method, is made. In addition, a multi-objective robust scenario-based stochastic programming approach is employed to cope with the operational uncertainty of the parameters. Finally, some numerical studies of the RSSCDP problem are conducted to demonstrate the capabilities and effectiveness of the developed model. The results depict a 10 to 15 percent improvement in the objectives. The findings confirm that the proposed resilience strategies are efficient in mitigating supply disruptions and can maintain the SC sustainability under disruptions.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10668-023-03769-x</doi><tpages>43</tpages><orcidid>https://orcid.org/0000-0002-7677-0840</orcidid><orcidid>https://orcid.org/0000-0002-7382-6351</orcidid><orcidid>https://orcid.org/0000-0002-4602-2710</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1573-2975
ispartof Environment, development and sustainability, 2024-11, Vol.26 (11), p.27485-27527
issn 1573-2975
1387-585X
1573-2975
language eng
recordid cdi_proquest_miscellaneous_3154160448
source SpringerLink Journals
subjects Absorptivity
Component and supplier management
Customers
Design
Design optimization
Disruption
Earth and Environmental Science
Ecology
Economic Geology
Economic Growth
Economics
Environment
Environmental Economics
Environmental Management
inventories
Inventory
Inventory management
Lot sizing
Multiple objective analysis
Optimization
Optimization models
Parameter robustness
Parameter uncertainty
Positioning
Production planning
Raw materials
Resilience
risk
Robustness
Stochastic programming
Suppliers
Supply
supply chain
Supply chain sustainability
Supply chains
Sustainability
Sustainable Development
transportation
Transportation planning
Uncertainty
title Resilient and sustainable supply chain design and planning under supply disruption risk using a multi-objective scenario-based robust optimization model
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T02%3A27%3A04IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Resilient%20and%20sustainable%20supply%20chain%20design%20and%20planning%20under%20supply%20disruption%20risk%20using%20a%20multi-objective%20scenario-based%20robust%20optimization%20model&rft.jtitle=Environment,%20development%20and%20sustainability&rft.au=Safari,%20Lida&rft.date=2024-11-01&rft.volume=26&rft.issue=11&rft.spage=27485&rft.epage=27527&rft.pages=27485-27527&rft.issn=1573-2975&rft.eissn=1573-2975&rft_id=info:doi/10.1007/s10668-023-03769-x&rft_dat=%3Cproquest_cross%3E3154160448%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3122871548&rft_id=info:pmid/&rfr_iscdi=true