Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems

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OriginalspracheEnglisch
Aufsatznummer5544
FachzeitschriftSustainability (Switzerland)
Jahrgang11
Ausgabenummer20
PublikationsstatusVeröffentlicht - 2 Okt. 2019

Abstract

The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.

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Individually Optimized Commercial Road Transport: A Decision Support System for Customizable Routing Problems. / Leyerer, Max; Sonneberg, Marc Oliver; Heumann, Maximilian et al.
in: Sustainability (Switzerland), Jahrgang 11, Nr. 20, 5544, 02.10.2019.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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abstract = "The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.",
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author = "Max Leyerer and Sonneberg, {Marc Oliver} and Maximilian Heumann and Tim Kammann and Breitner, {Michael H.}",
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AU - Leyerer, Max

AU - Sonneberg, Marc Oliver

AU - Heumann, Maximilian

AU - Kammann, Tim

AU - Breitner, Michael H.

N1 - Funding information: Acknowledgments: The publication of this article was funded by the Open Access fund of Leibniz Universität Hannover.

PY - 2019/10/2

Y1 - 2019/10/2

N2 - The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.

AB - The Vehicle Routing Problem (VRP) in its manifold variants is widely discussed in scientific literature. We investigate related optimization models and solution methods to determine the state of research for vehicle routing attributes and their combinations. Most of these approaches are idealized and focus on single problem-tailored routing applications. Addressing this research gap, we present a customizable VRP for optimized road transportation embedded into a Decision Support System (DSS). It integrates various model attributes and handles a multitude of real-world routing problems. In the context of urban logistics, practitioners of different industries and researchers are assisted in efficient route planning that allows for minimizing driving distances and reducing vehicle emissions. Based on the design science research methodology, we evaluate the DSS with computational benchmarks and real-world simulations. Results indicate that our developed DSS can compete with problem-tailored algorithms. With our solution-oriented DSS as final artifact, we contribute to an enhanced economic and environmental sustainability in urban logistic applications.

KW - Decision support system

KW - Design science research

KW - Green information system

KW - Urban logistics

KW - Vehicle routing problem

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DO - 10.3390/su11205544

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