Prof. Dr.-Ing. Carlos Jahn
Address
Hamburg University of Technology
Institute of Maritime Logistics
Am Schwarzenberg-Campus 4 (D)
21073 Hamburg
Contact Details
Office: building D room 5.002a
Registration via Ms. Beckmann (Room 5.003)
Phone: +49 40 42878 4450
Fax: +49 40 42731 4478
E-mail: carlos.jahn(at)tuhh(dot)de
ORCiD: 0000-0002-5409-0748
2024
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2023
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2022
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2021
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2020
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2019
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2018
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2017
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2016
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2015
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2014
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared
2013
[182422] |
Title: Defining the quota of truck appointment systems. <em>Data science and innovation in supply chain management : how data transforms the value chain // Proceedings of the Hamburg International Conference of Logistics (HICL)/ Data Science in Maritime and City Logistics</em> |
Written by: Lange, Ann-Kathrin and Kreuz, Felix and Langkau, Sven and Jahn, Carlos and Clausen, Uwe |
in: <em>HICL 2020</em>. (2020). |
Volume: Number: |
on pages: |
Chapter: |
Editor: In Jahn, Carlos and Kersten, Wolfgang and Ringle, Christian M. (Eds.) |
Publisher: epubli: |
Series: Proceedings of the Hamburg International Conference of Logistics (HICL) |
Address: Berlin |
Edition: |
ISBN: 978-3-753123-47-9 |
how published: |
Organization: |
School: |
Institution: |
Type: |
DOI: 10.15480/882.3148 |
URL: |
ARXIVID: |
PMID: |
Note:
Abstract: Purpose: Truck appointment systems (TAS) are a widely used method to alleviate peaks in truck arrivals at container terminals in seaports and in the hinterland. One big advantage is the opportunity to reduce operation costs for the terminals and the truck queue length in front of the terminal gate. This study aims to analyze and clas-sify different approaches used in science and industry to determine the quota of al-lowed trucks per time window. Methodology: A comprehensive systematic literature analysis is applied to identify the different approaches to determine the quota of time windows in science and in industry. Findings: The results of the study show that many approaches have been based on experience and are mostly used to improve individual terminals rather than the port as a whole. Methods used to improve and analyze interrelationships are mainly methods of mathematical optimization and simulation. Originality: The question under consideration was mostly only marginally consid-ered in existing investigations, even though it has a major impact on the success of a TAS. Furthermore, only individual solutions have been examined so far and not the suitability of the approaches compared