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Optimizing last-mile delivery

Authors: Kemnik, Timo;

Optimizing last-mile delivery

Abstract

Weltweit befindet sich der Warenverkehr in einem starken Wachstum, für das keine Trendwende in den nächsten Jahren prognostiziert wird. Neben dem starken Wachstum, insbesondere im E-Commerce, welches für die Logistikprozesse eine große Herausforderung sein würde, bieten die Unternehmen in dem stark umkämpften Markt zusätzlich immer weitere Serviceleistungen an, um sich von der Konkurrenz abzugrenzen. Insbesondere die immer kürzer werdenden Lieferzeiten stellen den individuellsten und damit kostenintensiven Teil, der letzten Meile des Logistikprozesses, vor eine große Herausforderung. Um diesen Herausforderungen zu begegnen, werden innovative Methoden entwickelt, wozu das im Rahmen dieser Arbeit untersuchte Modell der sogenannten hybriden Truck/Roboter-Zustellung gehört. Hierfür wird in dieser Arbeit ein heuristisches Modell von Ostermeier et al. (2022) weiterentwickelt, um die Lösungsqualität zu erhöhen und zusätzlich werden die Einflüsse verschiedener Parameter auf die Gesamtkosten untersucht. Im Rahmen dieser Weiterentwicklung zeigt sich, dass die Lösungsqualität im Vergleich zu dem Modell von Ostermeier et al. (2022) deutlich verbessert werden konnte. Die Ergebnisse zeigen zusätzlich, dass größere maximale Transportkapazitäten des Vans nicht zu geringen Gesamtkosten führen müssen und die Zusammensetzung des genutzten Datensatzes einen signifikanten Einfluss auf die Lösung hat. Die Ergebnisse lassen den Entschluss zu, dass in diesem Modell die individuellen zeitabhängigen operativen Kosten für den Van einen stärkeren Einfluss auf die Kostenstruktur haben als die individuellen zeitabhängigen Kosten der Roboter. Die Untersuchung hat zusätzlich ergeben, dass die distanzabhängigen Kosten in der Kostenstruktur einen höheren Einfluss haben als die zeitabhängigen Kosten.

The global transport of goods is experiencing strong growth, for which no trend reversal is forecast in the next several years. In addition to the strong growth, particularly in e-commerce, which would be a major challenge for logistics processes, companies in this highly competitive market are also offering an increasing number of additional services in order to set themselves apart from the competition. In particular, decreasing delivery times pose a major challenge for the most customized and therefore cost-intensive part of the logistics process, the last mile. Innovative methods are being developed to meet these challenges, including the so-called hybrid truck/robot delivery model analyzed in this thesis. For this purpose, a heuristic model by Ostermeier et al. (2022) is further developed in this thesis in order to increase the solution quality and, in addition, the influences of various parameters on the total costs are analyzed. This further development shows that the solution quality could be significantly improved compared to the model of Ostermeier et al. (2022). The results also reveal that larger maximum transport capacities of the van do not necessarily lead to lower total costs and that the composition of the data set used has a significant influence on the solution. The results allow the conclusion that in this model the individual time-dependent operational costs for the van have a stronger influence on the cost structure than the individual time-dependent costs of the robots. The study also showed that the distance-dependent costs have a greater influence on the cost structure than the time-dependent costs.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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