Prof. Dr.-Ing. Carlos Jahn

Adresse

Technische Universität Hamburg
Institut für Maritime Logistik
Am Schwarzenberg-Campus 4 (D)
21073 Hamburg

 

Kontaktdaten

Büro: Gebäude D Raum 5.002a
Anmeldung bei Fr. Beckmann (Raum 5.003)
Tel.: +49 40 42878 4450
Fax: +49 40 42731 4478
E-Mail: carlos.jahn(at)tuhh(dot)de
ORCiD: 0000-0002-5409-0748



Veröffentlichungen (Auszug)

2024

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2023

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2022

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2021

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2020

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2019

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2018

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2017

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2016

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2015

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2014

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable

2013

[182408]
Title: Integrated Simulation-Based Optimization of Operational Decisions at Container Terminals.
Written by: Kastner, Marvin and Nellen, Nicole and Schwientek, Anne and Jahn, Carlos
in: <em>Algorithms</em>. (2021).
Volume: <strong>14</strong>. Number: (2),
on pages:
Chapter:
Editor:
Publisher:
Series:
Address:
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI: 10.3390/a14020042
URL: https://www.mdpi.com/1999-4893/14/2/42
ARXIVID:
PMID:

[pdf] [www]

Note:

Abstract: At container terminals, many cargo handling processes are interconnected and occur in parallel. Within short time windows, many operational decisions need to be made and should consider both time efficiency and equipment utilization. During operation, many sources of disturbance and, thus, uncertainty exist. For these reasons, perfectly coordinated processes can potentially unravel. This study analyzes simulation-based optimization, an approach that considers uncertainty by means of simulation while optimizing a given objective. The developed procedure simultaneously scales the amount of utilized equipment and adjusts the selection and tuning of operational policies. Thus, the benefits of a simulation study and an integrated optimization framework are combined in a new way. Four meta-heuristics - Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search - guide the simulation-based optimization process. Thus, this study aims to determine a favorable configuration of equipment quantity and operational policies for container terminals using a small number of experiments and, simultaneously, to empirically compare the chosen meta-heuristics including the reproducibility of the optimization runs. The results show that simulation-based optimization is suitable for identifying the amount of required equipment and well-performing policies. Among the presented scenarios, no clear ranking between meta-heuristics regarding the solution quality exists. The approximated optima suggest that pooling yard trucks and a yard block assignment that is close to the quay crane are preferable