Publication:
Express shipments with autonomous robots and public transportation

dc.contributor.coauthorErmağan, Umut
dc.contributor.departmentDepartment of Industrial Engineering
dc.contributor.kuauthorYıldız, Barış
dc.contributor.kuauthorSalman, Fatma Sibel
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.date.accessioned2025-02-11T05:54:22Z
dc.date.available2025-02-10
dc.date.issued2024-12-01
dc.description.abstractGrowing urbanization, exploding e-commerce, heightened customer expectations, and the need to reduce the environmental impact of transportation ask for innovative last-mile delivery solutions. This paper explores a new express shipment model that combines public transportation with Autonomous Robots (ARs) and studies its real-time management. Under dynamic demand arrivals with short delivery time promises, we propose a rolling horizon framework and devise a machine learning-enhanced Column Generation (CG) methodology to solve the real-time AR dispatching problem. The results of our numerical experiments with real-world delivery demand data show the significant potential of the proposed system to reduce travel time, vehicle traffic, emissions, and noise. Our results also reveal the efficacy of the learning-based CG methodology, which provides almost the same quality solutions as the classical CG approach with much less computational effort.
dc.description.fulltextYes
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessGold OA
dc.description.peerreviewstatusPeer-Reviewed
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuEU
dc.description.sponsorshipThis study has been supported by the European Research Council (ERC) under grant number 101076231 as a part of the GoodMobility project (https://goodmobility.ku.edu.tr). This work would not have been possible without the assistance of the Trendyol Operations and Innovation Department. We thank them for providing us with real-life data and for informative discussions.
dc.description.versionPublished Version
dc.identifier.doi10.1016/j.tre.2024.103782
dc.identifier.eissn1878-5794
dc.identifier.embargoNo
dc.identifier.filenameinventorynoIR04634
dc.identifier.grantno10107623
dc.identifier.issn1366-5545
dc.identifier.issueDecember 2024
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85204888295
dc.identifier.urihttps://doi.org/10.1016/j.tre.2024.103782
dc.identifier.urihttps://hdl.handle.net/20.500.14288/26784
dc.identifier.volume192
dc.identifier.wos001326929400001
dc.keywordsExpress shipment
dc.keywordsPublic transportation
dc.keywordsAutonomous robots
dc.keywordsRolling horizon
dc.keywordsMachine learning
dc.keywordsSustainable logistics
dc.language.isoeng
dc.publisherElsevier
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofTransportation Research Part E: Logistics and Transportation Review
dc.relation.openaccessYes
dc.relation.projectA New Perspective on City Logistics: Concepts, Theory, and Models for Designing and Managing Logistics as a Service
dc.rightsCC BY-NC-ND (Attribution-NonCommercial-NoDerivs)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBusiness and economics
dc.subjectEngineering
dc.subjectOperations research and management science
dc.subjectTransportation
dc.titleExpress shipments with autonomous robots and public transportation
dc.typeJournal Article
dspace.entity.typePublication
relation.isOrgUnitOfPublicationd6d00f52-d22d-4653-99e7-863efcd47b4a
relation.isOrgUnitOfPublication.latestForDiscoveryd6d00f52-d22d-4653-99e7-863efcd47b4a
relation.isParentOrgUnitOfPublication8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isParentOrgUnitOfPublication.latestForDiscovery8e756b23-2d4a-4ce8-b1b3-62c794a8c164
relation.isProjectOfPublication4a4dcae1-6c73-44e3-b970-bc079a6216bc
relation.isProjectOfPublication.latestForDiscovery4a4dcae1-6c73-44e3-b970-bc079a6216bc

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
IR04634.pdf
Size:
1.62 MB
Format:
Adobe Portable Document Format