Publication: Express shipments with autonomous robots and public transportation
dc.contributor.coauthor | Ermağan, Umut | |
dc.contributor.department | Department of Industrial Engineering | |
dc.contributor.kuauthor | Yıldız, Barış | |
dc.contributor.kuauthor | Salman, Fatma Sibel | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.date.accessioned | 2025-02-11T05:54:22Z | |
dc.date.available | 2025-02-10 | |
dc.date.issued | 2024-12-01 | |
dc.description.abstract | Growing 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.fulltext | Yes | |
dc.description.indexedby | WOS | |
dc.description.indexedby | Scopus | |
dc.description.openaccess | Gold OA | |
dc.description.peerreviewstatus | Peer-Reviewed | |
dc.description.publisherscope | International | |
dc.description.readpublish | N/A | |
dc.description.sponsoredbyTubitakEu | EU | |
dc.description.sponsorship | This 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.version | Published Version | |
dc.identifier.doi | 10.1016/j.tre.2024.103782 | |
dc.identifier.eissn | 1878-5794 | |
dc.identifier.embargo | No | |
dc.identifier.filenameinventoryno | IR04634 | |
dc.identifier.grantno | 10107623 | |
dc.identifier.issn | 1366-5545 | |
dc.identifier.issue | December 2024 | |
dc.identifier.quartile | Q1 | |
dc.identifier.scopus | 2-s2.0-85204888295 | |
dc.identifier.uri | https://doi.org/10.1016/j.tre.2024.103782 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/26784 | |
dc.identifier.volume | 192 | |
dc.identifier.wos | 001326929400001 | |
dc.keywords | Express shipment | |
dc.keywords | Public transportation | |
dc.keywords | Autonomous robots | |
dc.keywords | Rolling horizon | |
dc.keywords | Machine learning | |
dc.keywords | Sustainable logistics | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.relation.affiliation | Koç University | |
dc.relation.collection | Koç University Institutional Repository | |
dc.relation.ispartof | Transportation Research Part E: Logistics and Transportation Review | |
dc.relation.openaccess | Yes | |
dc.relation.project | A New Perspective on City Logistics: Concepts, Theory, and Models for Designing and Managing Logistics as a Service | |
dc.rights | CC BY-NC-ND (Attribution-NonCommercial-NoDerivs) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Business and economics | |
dc.subject | Engineering | |
dc.subject | Operations research and management science | |
dc.subject | Transportation | |
dc.title | Express shipments with autonomous robots and public transportation | |
dc.type | Journal Article | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | d6d00f52-d22d-4653-99e7-863efcd47b4a | |
relation.isOrgUnitOfPublication.latestForDiscovery | d6d00f52-d22d-4653-99e7-863efcd47b4a | |
relation.isParentOrgUnitOfPublication | 8e756b23-2d4a-4ce8-b1b3-62c794a8c164 | |
relation.isParentOrgUnitOfPublication.latestForDiscovery | 8e756b23-2d4a-4ce8-b1b3-62c794a8c164 | |
relation.isProjectOfPublication | 4a4dcae1-6c73-44e3-b970-bc079a6216bc | |
relation.isProjectOfPublication.latestForDiscovery | 4a4dcae1-6c73-44e3-b970-bc079a6216bc |
Files
Original bundle
1 - 1 of 1