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A combined fleet size and mix vehicle routing model for last-mile distribution in disaster relief

Eberhardt, Katharina ORCID iD icon 1; Diehlmann, Florian; Lüttenberg, Markus ORCID iD icon 1; Kaiser, Florian Klaus 1; Schultmann, Frank ORCID iD icon 1
1 Institut für Industriebetriebslehre und Industrielle Produktion (IIP), Karlsruher Institut für Technologie (KIT)

Abstract:

Disasters pose a significant challenge for last-mile operations, straining emergency logistics systems' ability to provide efficient aid and support. In this context, a Fleet Size and Mix Vehicle Routing Problem for Disaster Management (FSMVRP-DM) is formulated, incorporating a fleet composition decision tailored to the specifics of disaster relief logistics. The model aims to optimize routing and analyze fleet decisions to minimize the sum of operating costs and population deprivation costs. Moreover, a prioritization approach is introduced to monitor deprivation time during transport resource scarcity, adjusting routes periodically to prevent extended supply gaps and minimize suffering costs. In addition, a case study is conducted in the German state of Baden-Württemberg to illustrate the potential applicability of the model. The findings highlight the advantages of integrating diverse and innovative fleet types, such as drones, and prioritizing the supply of multiple demand points when resources are scarce. Overall, the research offers decision support for authorities by enhancing information transparency, facilitating resource management, strengthening the effectiveness of disaster response capabilities, and providing resilient and adaptive strategies for last-mile distribution.


Verlagsausgabe §
DOI: 10.5445/IR/1000180228
Veröffentlicht am 20.03.2025
Originalveröffentlichung
DOI: 10.1016/j.pdisas.2025.100411
Scopus
Zitationen: 1
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion – Deutsch-Französisches Institut für Umweltforschung (DFIU)
Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 04.2025
Sprache Englisch
Identifikator ISSN: 2590-0617
KITopen-ID: 1000180228
Erschienen in Progress in Disaster Science
Verlag Elsevier
Band 26
Seiten 100411
Nachgewiesen in Dimensions
Scopus
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