Marvin Kastner, M.Sc.

Address

Hamburg University of Technology
Institute of Maritime Logistics
Am Schwarzenberg-Campus 4 (D)
21073 Hamburg

 

Contact Details & Profiles

Office: building D room 5.007
Phone: +49 40 42878 4793
E-mail: marvin.kastner(at)tuhh(dot)de
ORCiD: 0000-0001-8289-2943
LinkedIn: https://www.linkedin.com/in/marvin-kastner/
ResearchGate: https://www.researchgate.net/profile/Marvin-Kastner
Google scholar: https://scholar.google.de/citations?user=lAR-oVAAAAAJ&hl=de&oi=ao
Scopus: https://www.scopus.com/authid/detail.uri?authorId=57221938031



Research Focus

  • Simulation-based Design of Container Terminals
  • Optimization of Yard Operations at Container Terminals
  • Data-driven Improvement of Maritime Security
  • Machine Learning in Maritime Logistic
  • Optimization of Multivariate Black-box Functions

Presentations and workshops (Excerpt)

  • 26.09.2024 a talk at the Hamburg International Conference of Logistics (HICL): "Hinterland rail connectivity of seaport container terminals" with the coauthors Owais Ahmed Shaikh, Yasser Shaikh, and Anish Sundar Gowthaman
  • 06.05.2024 a workshop at the Graduate Academy of TUHH: "Introduction to Jupyter Notebooks" (title translated) [more]
  • 25.01.2023 a talk at the 7. Suderburger Logistics Forum: "AI-assisted planning of cargo handling facilities with the example of container terminals" (title translated)
  • 15.09.2022 a talk at the MLE-Days 2022: "Synthetic data for reinforcement learning in container terminal control systems."
  • 28.06.2022 a workshop at the Graduate Academy of TUHH: "Introduction to Jupyter Notebooks" (title translated) [more]
  • 02.07.2021 a workshop at the MLE-Days 2021: "Machine Learning in Maritime Logistics" (title translated) [zip]
  • 16.03.2021 a workshop at the Graduate Academy of TUHH: "Introduction to Jupyter Notebooks" (title translated) [more]
  • 30.11.2020 in the lecture series "Train Your Engineering Network" of the MLE initiative: "How to Talk About Machine Learning with Jupyter Notebooks"
  • 22.11.2019 at DISRUPT NOW! AI for Hamburg: "Artificial Intelligence in Maritime Economy" (title translated) [more]
  • 29.10.2019 in the context of forschungsbörse: "Maritime Logistics - an all-round cover" (title translated) [more]
  • 23.10.2019 at the Open Access Week 2019 at TUHH: "Data Analysis - Describe and Visualize Data with Jupyter Notebooks" (title translated) [more] [git]
  • 16.11.2018 at the GI DevCamp Hamburg: "Mobility Research and GDPR"
  • 27.09.2018 at SGKV WG regarding truck arrivals: "Forecasting and Neural Networks – What is possible?" (title translated)


Publications (Excerpt)

2024

[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

2023

[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

2022

[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

2021

[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

2020
[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.

2019

[191075]
Title: On Estimating the Required Yard Capacity for Container Terminals. <em>Dynamics in Logistics</em>
Written by: Édes, Luc and Kastner, Marvin and Jahn, Carlos
in: (2024).
Volume: Number:
on pages: 171-182
Chapter:
Editor: In Freitag, Michael and Kinra, Aseem and Kotzab, Herbert and Megow, Nicole (Eds.)
Publisher: Springer, Cham and Springer Nature Switzerland:
Series:
Address: Cham
Edition:
ISBN: 978-3-031-56826-8
how published:
Organization:
School:
Institution:
Type:
DOI: 10.1007/978-3-031-56826-8_13
URL: https://link.springer.com/chapter/10.1007/978-3-031-56826-8_13
ARXIVID:
PMID:

[www]

Note: conflowgen

Abstract: Vessel delays and increased terminal call sizes negatively impact the ability to properly plan daily operations at seaport container terminals. Such traffic patterns lead to, among others, infrequent peak loads at the seaside of container terminals, complicating terminal operations. Thus, relying on annual or monthly statistics fails to account for these day-to-day fluctuations. When container terminals are planned, be it a greenfield or brownfield terminal, these variations in operations need to be accounted for. The traditional formula-based approach to design terminals uses annual statistics. In this study, it is first used to produce estimates for the required yard capacity for three existing exemplary container terminals. These are then compared to the results of numerical experiments using the synthetic container flow generator ConFlowGen. The findings reveal that yard capacity requirements fluctuate considerably depending on the timing of vessel arrivals and their call sizes. This dynamic modeling proved particularly beneficial for planning gateway traffic, offering more accurate storage capacity predictions. Suggestions are made for how to further develop ConFlowGen for handling transshipment traffic better in future versions.