Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration
In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes...
Gespeichert in:
Veröffentlicht in: | Sustainability 2022-08, Vol.14 (16), p.10281 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 16 |
container_start_page | 10281 |
container_title | Sustainability |
container_volume | 14 |
creator | Kaoud, Essam Abdel-Aal, Mohammad A. M Sakaguchi, Tatsuhiko Uchiyama, Naoki |
description | In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction). |
doi_str_mv | 10.3390/su141610281 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2706445132</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A746959526</galeid><sourcerecordid>A746959526</sourcerecordid><originalsourceid>FETCH-LOGICAL-c371t-dac64123a04b654f9ff2f410b6923916f3a6dd66afad68fd6417bc7a8ed5ed53</originalsourceid><addsrcrecordid>eNpVkVFLwzAQx4soKOqTXyDgk0hn0rTp-qhF52AwcXsvaXOpGW1Sk1SdX8EvbXQ-uLuDO47f_47jouiC4AmlBb5xI0kJIziZkoPoJME5iQnO8OG_-jg6d26Dg1FKCsJOoq9nU4_Oo-XgVa8-uVdGI2ks4uhOxct6A41Xb4BmFkCjsjMORLwwZkCrcRi6LSpfuNLoXfkX9AgerGlBgxkdWluu3WCs381cbZ2HHnEt0JMFF_pKt6g02ikB9pc5i44k7xyc_-XTaP1wvy4f48VyNi9vF3FDc-JjwRuWkoRynNYsS2UhZSJTgmtWJDQcJSlnQjDGJRdsKkWA87rJ-RREFoKeRpe7sYM1ryM4X23MaHXYWCU5ZmmaEZoEarKjWt5BpbQ03vImuIBeNUaDVKF_m6esyIosYUFwtScIjIcP3_LRuWq-et5nr3dsY41zFmQ1WNVzu60Irn6eWf17Jv0GTSmTNA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2706445132</pqid></control><display><type>article</type><title>Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Kaoud, Essam ; Abdel-Aal, Mohammad A. M ; Sakaguchi, Tatsuhiko ; Uchiyama, Naoki</creator><creatorcontrib>Kaoud, Essam ; Abdel-Aal, Mohammad A. M ; Sakaguchi, Tatsuhiko ; Uchiyama, Naoki</creatorcontrib><description>In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction).</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su141610281</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algorithms ; Carbon ; Computer applications ; Costs ; Customers ; Emissions ; Environmental aspects ; Linear programming ; Logistics ; Mathematical optimization ; Methods ; Optimization ; Optimization models ; Parameter uncertainty ; Supply chains ; Sustainability ; Transportation ; Transportation systems</subject><ispartof>Sustainability, 2022-08, Vol.14 (16), p.10281</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c371t-dac64123a04b654f9ff2f410b6923916f3a6dd66afad68fd6417bc7a8ed5ed53</citedby><cites>FETCH-LOGICAL-c371t-dac64123a04b654f9ff2f410b6923916f3a6dd66afad68fd6417bc7a8ed5ed53</cites><orcidid>0000-0002-6367-2598 ; 0000-0002-0919-9699</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Kaoud, Essam</creatorcontrib><creatorcontrib>Abdel-Aal, Mohammad A. M</creatorcontrib><creatorcontrib>Sakaguchi, Tatsuhiko</creatorcontrib><creatorcontrib>Uchiyama, Naoki</creatorcontrib><title>Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration</title><title>Sustainability</title><description>In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction).</description><subject>Algorithms</subject><subject>Carbon</subject><subject>Computer applications</subject><subject>Costs</subject><subject>Customers</subject><subject>Emissions</subject><subject>Environmental aspects</subject><subject>Linear programming</subject><subject>Logistics</subject><subject>Mathematical optimization</subject><subject>Methods</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>Parameter uncertainty</subject><subject>Supply chains</subject><subject>Sustainability</subject><subject>Transportation</subject><subject>Transportation systems</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpVkVFLwzAQx4soKOqTXyDgk0hn0rTp-qhF52AwcXsvaXOpGW1Sk1SdX8EvbXQ-uLuDO47f_47jouiC4AmlBb5xI0kJIziZkoPoJME5iQnO8OG_-jg6d26Dg1FKCsJOoq9nU4_Oo-XgVa8-uVdGI2ks4uhOxct6A41Xb4BmFkCjsjMORLwwZkCrcRi6LSpfuNLoXfkX9AgerGlBgxkdWluu3WCs381cbZ2HHnEt0JMFF_pKt6g02ikB9pc5i44k7xyc_-XTaP1wvy4f48VyNi9vF3FDc-JjwRuWkoRynNYsS2UhZSJTgmtWJDQcJSlnQjDGJRdsKkWA87rJ-RREFoKeRpe7sYM1ryM4X23MaHXYWCU5ZmmaEZoEarKjWt5BpbQ03vImuIBeNUaDVKF_m6esyIosYUFwtScIjIcP3_LRuWq-et5nr3dsY41zFmQ1WNVzu60Irn6eWf17Jv0GTSmTNA</recordid><startdate>20220801</startdate><enddate>20220801</enddate><creator>Kaoud, Essam</creator><creator>Abdel-Aal, Mohammad A. M</creator><creator>Sakaguchi, Tatsuhiko</creator><creator>Uchiyama, Naoki</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-6367-2598</orcidid><orcidid>https://orcid.org/0000-0002-0919-9699</orcidid></search><sort><creationdate>20220801</creationdate><title>Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration</title><author>Kaoud, Essam ; Abdel-Aal, Mohammad A. M ; Sakaguchi, Tatsuhiko ; Uchiyama, Naoki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c371t-dac64123a04b654f9ff2f410b6923916f3a6dd66afad68fd6417bc7a8ed5ed53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Carbon</topic><topic>Computer applications</topic><topic>Costs</topic><topic>Customers</topic><topic>Emissions</topic><topic>Environmental aspects</topic><topic>Linear programming</topic><topic>Logistics</topic><topic>Mathematical optimization</topic><topic>Methods</topic><topic>Optimization</topic><topic>Optimization models</topic><topic>Parameter uncertainty</topic><topic>Supply chains</topic><topic>Sustainability</topic><topic>Transportation</topic><topic>Transportation systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kaoud, Essam</creatorcontrib><creatorcontrib>Abdel-Aal, Mohammad A. M</creatorcontrib><creatorcontrib>Sakaguchi, Tatsuhiko</creatorcontrib><creatorcontrib>Uchiyama, Naoki</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kaoud, Essam</au><au>Abdel-Aal, Mohammad A. M</au><au>Sakaguchi, Tatsuhiko</au><au>Uchiyama, Naoki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration</atitle><jtitle>Sustainability</jtitle><date>2022-08-01</date><risdate>2022</risdate><volume>14</volume><issue>16</issue><spage>10281</spage><pages>10281-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction).</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su141610281</doi><orcidid>https://orcid.org/0000-0002-6367-2598</orcidid><orcidid>https://orcid.org/0000-0002-0919-9699</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2071-1050 |
ispartof | Sustainability, 2022-08, Vol.14 (16), p.10281 |
issn | 2071-1050 2071-1050 |
language | eng |
recordid | cdi_proquest_journals_2706445132 |
source | MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Algorithms Carbon Computer applications Costs Customers Emissions Environmental aspects Linear programming Logistics Mathematical optimization Methods Optimization Optimization models Parameter uncertainty Supply chains Sustainability Transportation Transportation systems |
title | Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T23%3A55%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Robust%20Optimization%20for%20a%20Bi-Objective%20Green%20Closed-Loop%20Supply%20Chain%20with%20Heterogeneous%20Transportation%20System%20and%20Presorting%20Consideration&rft.jtitle=Sustainability&rft.au=Kaoud,%20Essam&rft.date=2022-08-01&rft.volume=14&rft.issue=16&rft.spage=10281&rft.pages=10281-&rft.issn=2071-1050&rft.eissn=2071-1050&rft_id=info:doi/10.3390/su141610281&rft_dat=%3Cgale_proqu%3EA746959526%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2706445132&rft_id=info:pmid/&rft_galeid=A746959526&rfr_iscdi=true |