A systematic review of modeling approaches in green supply chain optimization
Over the past decade, the significance of optimizing green supply chain management (GSCM) has gained unprecedented attention from both scholars and industry professionals. This surge in interest has led researchers to employ diverse modeling approaches in the pursuit of enhancing green supply chain...
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| Veröffentlicht in: | Environmental science and pollution research international 2023-11, Vol.30 (53), p.113218-113241 |
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| creator | Xames, Md Doulotuzzaman Shefa, Jannatul Azrin, Fahima Akter Uddin, Abu Saleh Md. Nakib Habiba, Umme Zaman, Washima |
| description | Over the past decade, the significance of optimizing green supply chain management (GSCM) has gained unprecedented attention from both scholars and industry professionals. This surge in interest has led researchers to employ diverse modeling approaches in the pursuit of enhancing green supply chain networks. In this systematic review, we analyze 159 recent GSCM optimization papers published from 2017 to 2022 and identify the recent trends in mathematical modeling, multi-objective optimization, and the modeling/solver tools utilized. We find that the primary green focus is on minimizing carbon emissions (
n
=
44
), reflecting the increasing concern for environmental sustainability. Among the modeling approaches employed, mixed-integer linear programming has emerged as the most popular choice (
n
=
51
), followed by game theory-based modeling (
n
=
30
). When it comes to multiobjective optimization, the ε-constraint approach is the most widely used. Evolutionary algorithms have emerged as the dominant meta-heuristic optimization approach. Additionally, the widely utilized solver in this domain is CPLEX with the most popular modeling/solver combination being GAMS/CPLEX. Moreover, the
Journal of Cleaner Production
was the leading outlet for research in this domain (
n
=
35
). In addition to these findings, this study also discusses some other research trends and future research directions. Finally, we discuss the theoretical, managerial, and policy implications of this study. By providing GSCM researchers and practitioners with the latest trends in GSCM optimization approaches, this study contributes to the further advancement of the field. |
| doi_str_mv | 10.1007/s11356-023-30396-w |
| format | Article |
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n
=
44
), reflecting the increasing concern for environmental sustainability. Among the modeling approaches employed, mixed-integer linear programming has emerged as the most popular choice (
n
=
51
), followed by game theory-based modeling (
n
=
30
). When it comes to multiobjective optimization, the ε-constraint approach is the most widely used. Evolutionary algorithms have emerged as the dominant meta-heuristic optimization approach. Additionally, the widely utilized solver in this domain is CPLEX with the most popular modeling/solver combination being GAMS/CPLEX. Moreover, the
Journal of Cleaner Production
was the leading outlet for research in this domain (
n
=
35
). In addition to these findings, this study also discusses some other research trends and future research directions. Finally, we discuss the theoretical, managerial, and policy implications of this study. By providing GSCM researchers and practitioners with the latest trends in GSCM optimization approaches, this study contributes to the further advancement of the field.</description><identifier>ISSN: 1614-7499</identifier><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-023-30396-w</identifier><identifier>PMID: 37861832</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; carbon ; domain ; Earth and Environmental Science ; Ecotoxicology ; Emissions ; Environment ; Environmental Chemistry ; Environmental Health ; environmental sustainability ; Evolutionary algorithms ; Game Theory ; Heuristic methods ; Industry ; Integer programming ; issues and policy ; Linear programming ; Mathematical models ; Mixed integer ; Models, Theoretical ; Multiple objective analysis ; Optimization ; Review Article ; Solvers ; supply chain ; supply chain management ; Supply chain sustainability ; Supply chains ; Systematic review ; Trends ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Environmental science and pollution research international, 2023-11, Vol.30 (53), p.113218-113241</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 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><rights>2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-33fc4068238f513e9215330a778e1bf2649942d78dec0738c6035aae311ea0783</cites><orcidid>0000-0001-8755-5778</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/s11356-023-30396-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-023-30396-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37861832$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xames, Md Doulotuzzaman</creatorcontrib><creatorcontrib>Shefa, Jannatul</creatorcontrib><creatorcontrib>Azrin, Fahima Akter</creatorcontrib><creatorcontrib>Uddin, Abu Saleh Md. Nakib</creatorcontrib><creatorcontrib>Habiba, Umme</creatorcontrib><creatorcontrib>Zaman, Washima</creatorcontrib><title>A systematic review of modeling approaches in green supply chain optimization</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>Over the past decade, the significance of optimizing green supply chain management (GSCM) has gained unprecedented attention from both scholars and industry professionals. This surge in interest has led researchers to employ diverse modeling approaches in the pursuit of enhancing green supply chain networks. In this systematic review, we analyze 159 recent GSCM optimization papers published from 2017 to 2022 and identify the recent trends in mathematical modeling, multi-objective optimization, and the modeling/solver tools utilized. We find that the primary green focus is on minimizing carbon emissions (
n
=
44
), reflecting the increasing concern for environmental sustainability. Among the modeling approaches employed, mixed-integer linear programming has emerged as the most popular choice (
n
=
51
), followed by game theory-based modeling (
n
=
30
). When it comes to multiobjective optimization, the ε-constraint approach is the most widely used. Evolutionary algorithms have emerged as the dominant meta-heuristic optimization approach. Additionally, the widely utilized solver in this domain is CPLEX with the most popular modeling/solver combination being GAMS/CPLEX. Moreover, the
Journal of Cleaner Production
was the leading outlet for research in this domain (
n
=
35
). In addition to these findings, this study also discusses some other research trends and future research directions. Finally, we discuss the theoretical, managerial, and policy implications of this study. By providing GSCM researchers and practitioners with the latest trends in GSCM optimization approaches, this study contributes to the further advancement of the field.</description><subject>Algorithms</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>carbon</subject><subject>domain</subject><subject>Earth and Environmental Science</subject><subject>Ecotoxicology</subject><subject>Emissions</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>environmental sustainability</subject><subject>Evolutionary algorithms</subject><subject>Game Theory</subject><subject>Heuristic methods</subject><subject>Industry</subject><subject>Integer programming</subject><subject>issues and policy</subject><subject>Linear programming</subject><subject>Mathematical models</subject><subject>Mixed integer</subject><subject>Models, Theoretical</subject><subject>Multiple objective analysis</subject><subject>Optimization</subject><subject>Review Article</subject><subject>Solvers</subject><subject>supply chain</subject><subject>supply chain management</subject><subject>Supply chain sustainability</subject><subject>Supply chains</subject><subject>Systematic review</subject><subject>Trends</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1614-7499</issn><issn>0944-1344</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkc1OGzEURq2KqkDaF-gCWWLTzYCvb8b2LCMEBSmITbu2HOdOMmj-as80Ck-PQ9KCuigrW_b5jq_1MfYVxAUIoS8jAOYqExIzFFiobPOBnYCCaaanRXH0Zn_MTmN8FEKKQupP7Bi1UWBQnrD7GY_bOFDjhsrzQL8r2vCu5E23pLpqV9z1feicX1PkVctXgajlcez7esv92qWjrh-qpnpK-a79zD6Wro705bBO2M-b6x9Xt9n84fvd1WyeecyLIUMs_VQoI9GUOSAVEnJE4bQ2BItSqjTyVC61WZIXGo1XAnPnCAHICW1wwr7tvWm2XyPFwTZV9FTXrqVujBaTL1c6N_m7qDRGgEADO-v5P-hjN4Y2fSRRBRRag1aJknvKhy7GQKXtQ9W4sLUg7K4Xu-_Fpl7sSy92k0JnB_W4aGj5N_KniATgHojpql1ReH37P9pnN9qXKQ</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Xames, Md Doulotuzzaman</creator><creator>Shefa, Jannatul</creator><creator>Azrin, Fahima Akter</creator><creator>Uddin, Abu Saleh Md. 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Nakib</au><au>Habiba, Umme</au><au>Zaman, Washima</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A systematic review of modeling approaches in green supply chain optimization</atitle><jtitle>Environmental science and pollution research international</jtitle><stitle>Environ Sci Pollut Res</stitle><addtitle>Environ Sci Pollut Res Int</addtitle><date>2023-11-01</date><risdate>2023</risdate><volume>30</volume><issue>53</issue><spage>113218</spage><epage>113241</epage><pages>113218-113241</pages><issn>1614-7499</issn><issn>0944-1344</issn><eissn>1614-7499</eissn><abstract>Over the past decade, the significance of optimizing green supply chain management (GSCM) has gained unprecedented attention from both scholars and industry professionals. This surge in interest has led researchers to employ diverse modeling approaches in the pursuit of enhancing green supply chain networks. In this systematic review, we analyze 159 recent GSCM optimization papers published from 2017 to 2022 and identify the recent trends in mathematical modeling, multi-objective optimization, and the modeling/solver tools utilized. We find that the primary green focus is on minimizing carbon emissions (
n
=
44
), reflecting the increasing concern for environmental sustainability. Among the modeling approaches employed, mixed-integer linear programming has emerged as the most popular choice (
n
=
51
), followed by game theory-based modeling (
n
=
30
). When it comes to multiobjective optimization, the ε-constraint approach is the most widely used. Evolutionary algorithms have emerged as the dominant meta-heuristic optimization approach. Additionally, the widely utilized solver in this domain is CPLEX with the most popular modeling/solver combination being GAMS/CPLEX. Moreover, the
Journal of Cleaner Production
was the leading outlet for research in this domain (
n
=
35
). In addition to these findings, this study also discusses some other research trends and future research directions. Finally, we discuss the theoretical, managerial, and policy implications of this study. By providing GSCM researchers and practitioners with the latest trends in GSCM optimization approaches, this study contributes to the further advancement of the field.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>37861832</pmid><doi>10.1007/s11356-023-30396-w</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0001-8755-5778</orcidid></addata></record> |
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| subjects | Algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution carbon domain Earth and Environmental Science Ecotoxicology Emissions Environment Environmental Chemistry Environmental Health environmental sustainability Evolutionary algorithms Game Theory Heuristic methods Industry Integer programming issues and policy Linear programming Mathematical models Mixed integer Models, Theoretical Multiple objective analysis Optimization Review Article Solvers supply chain supply chain management Supply chain sustainability Supply chains Systematic review Trends Waste Water Technology Water Management Water Pollution Control |
| title | A systematic review of modeling approaches in green supply chain optimization |
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