Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping

Beizhen Jia; Niels Gorm Malý Rytter; Line Blander Reinhardt; Gauvain Haulot; Mads Bentzen Billesø

doi:10.1007/978-3-030-31140-7_8

Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping

Beizhen Jia^*, Niels Gorm Malý Rytter, Line Blander Reinhardt, Gauvain Haulot, Mads Bentzen Billesø

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

4 Citations (Scopus)

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Abstract

Ro-Ro shipping is a dominant form of short sea freight transport. Ro-Ro ship operators are today unable to provide customers with precise information about when trailers are available for pick-up by customers on the terminal despite vessel arrival times being well known in due time. This results in reduced truck utilization, longer waiting time for drivers, less efficient yard space utilization, potential terminal congestion and dissatisfied customers. In this paper the cargo unit discharge time estimation problem of Ro-Ro shipping is solved in collaboration with a European short-sea Ro-Ro shipping company. A module-based framework using statistical analysis for estimating the discharge time is proposed and tested. The initial framework is able to estimate the earliest pick-up time of each individual truck or trailer within 1 h accuracy for up to 70% of all cargo. The results of the study show potential for improving performance and accuracy. Further investigation and testing is currently ongoing by the case company based on the results from this study.

Original language	English
Title of host publication	Computational Logistics - 10th International Conference, ICCL 2019, Proceedings
Editors	Carlos Paternina-Arboleda, Stefan Voß
Number of pages	14
Publisher	Springer
Publication date	2019
Pages	122-135
ISBN (Print)	9783030311391
DOIs	https://doi.org/10.1007/978-3-030-31140-7_8
Publication status	Published - 2019
Event	10th International Conference on Computational Logistics, ICCL 2019 - Barranquilla, Colombia Duration: 30 Sept 2019 → 2 Oct 2019

Conference

Conference	10th International Conference on Computational Logistics, ICCL 2019
Country/Territory	Colombia
City	Barranquilla
Period	30/09/2019 → 02/10/2019

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11756
ISSN	0302-9743

Keywords

Cargo discharge time estimation
Industry implementation
Integrated logistics chain
Short sea shipping
Terminal operations

Access to Document

10.1007/978-3-030-31140-7_8

Manuscript for ICCL 2019 - Estimating Discharging Time of Cargo Units A Case of Ro-Ro ShippingAccepted author manuscript, 679 KB

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Cite this

Jia, Beizhen ; Rytter, Niels Gorm Malý ; Reinhardt, Line Blander et al. / Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping. Computational Logistics - 10th International Conference, ICCL 2019, Proceedings. editor / Carlos Paternina-Arboleda ; Stefan Voß. Springer, 2019. pp. 122-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11756).

@inproceedings{1ed32602674f47d8adce4cd58002eea1,

title = "Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping",

abstract = "Ro-Ro shipping is a dominant form of short sea freight transport. Ro-Ro ship operators are today unable to provide customers with precise information about when trailers are available for pick-up by customers on the terminal despite vessel arrival times being well known in due time. This results in reduced truck utilization, longer waiting time for drivers, less efficient yard space utilization, potential terminal congestion and dissatisfied customers. In this paper the cargo unit discharge time estimation problem of Ro-Ro shipping is solved in collaboration with a European short-sea Ro-Ro shipping company. A module-based framework using statistical analysis for estimating the discharge time is proposed and tested. The initial framework is able to estimate the earliest pick-up time of each individual truck or trailer within 1 h accuracy for up to 70% of all cargo. The results of the study show potential for improving performance and accuracy. Further investigation and testing is currently ongoing by the case company based on the results from this study.",

keywords = "Cargo discharge time estimation, Industry implementation, Integrated logistics chain, Short sea shipping, Terminal operations",

author = "Beizhen Jia and Rytter, {Niels Gorm Mal{\'y}} and Reinhardt, {Line Blander} and Gauvain Haulot and Billes{\o}, {Mads Bentzen}",

note = "Funding Information: Acknowledgements. We would like to thank our industrial partner DFDS for its openness on problems and data sharing, and all the help and support from DFDS in Copenhagen, Vlaardingen and Immingham. The research is funded by EU Baltic Sea Interreg project – ECOPRODIGI, aiming at improving eco-efficiency in shipping industry processes through digitalization. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 10th International Conference on Computational Logistics, ICCL 2019 ; Conference date: 30-09-2019 Through 02-10-2019",

year = "2019",

doi = "10.1007/978-3-030-31140-7_8",

language = "English",

isbn = "9783030311391",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "122--135",

editor = "Carlos Paternina-Arboleda and Stefan Vo{\ss}",

booktitle = "Computational Logistics - 10th International Conference, ICCL 2019, Proceedings",

address = "Germany",

}

Jia, B, Rytter, NGM, Reinhardt, LB, Haulot, G & Billesø, MB 2019, Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping. in C Paternina-Arboleda & S Voß (eds), Computational Logistics - 10th International Conference, ICCL 2019, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11756, pp. 122-135, 10th International Conference on Computational Logistics, ICCL 2019, Barranquilla, Colombia, 30/09/2019. https://doi.org/10.1007/978-3-030-31140-7_8

Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping. / Jia, Beizhen; Rytter, Niels Gorm Malý; Reinhardt, Line Blander et al.
Computational Logistics - 10th International Conference, ICCL 2019, Proceedings. ed. / Carlos Paternina-Arboleda; Stefan Voß. Springer, 2019. p. 122-135 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11756).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

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AU - Jia, Beizhen

AU - Rytter, Niels Gorm Malý

AU - Reinhardt, Line Blander

AU - Haulot, Gauvain

AU - Billesø, Mads Bentzen

N1 - Funding Information: Acknowledgements. We would like to thank our industrial partner DFDS for its openness on problems and data sharing, and all the help and support from DFDS in Copenhagen, Vlaardingen and Immingham. The research is funded by EU Baltic Sea Interreg project – ECOPRODIGI, aiming at improving eco-efficiency in shipping industry processes through digitalization. Publisher Copyright: © Springer Nature Switzerland AG 2019. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2019

Y1 - 2019

N2 - Ro-Ro shipping is a dominant form of short sea freight transport. Ro-Ro ship operators are today unable to provide customers with precise information about when trailers are available for pick-up by customers on the terminal despite vessel arrival times being well known in due time. This results in reduced truck utilization, longer waiting time for drivers, less efficient yard space utilization, potential terminal congestion and dissatisfied customers. In this paper the cargo unit discharge time estimation problem of Ro-Ro shipping is solved in collaboration with a European short-sea Ro-Ro shipping company. A module-based framework using statistical analysis for estimating the discharge time is proposed and tested. The initial framework is able to estimate the earliest pick-up time of each individual truck or trailer within 1 h accuracy for up to 70% of all cargo. The results of the study show potential for improving performance and accuracy. Further investigation and testing is currently ongoing by the case company based on the results from this study.

AB - Ro-Ro shipping is a dominant form of short sea freight transport. Ro-Ro ship operators are today unable to provide customers with precise information about when trailers are available for pick-up by customers on the terminal despite vessel arrival times being well known in due time. This results in reduced truck utilization, longer waiting time for drivers, less efficient yard space utilization, potential terminal congestion and dissatisfied customers. In this paper the cargo unit discharge time estimation problem of Ro-Ro shipping is solved in collaboration with a European short-sea Ro-Ro shipping company. A module-based framework using statistical analysis for estimating the discharge time is proposed and tested. The initial framework is able to estimate the earliest pick-up time of each individual truck or trailer within 1 h accuracy for up to 70% of all cargo. The results of the study show potential for improving performance and accuracy. Further investigation and testing is currently ongoing by the case company based on the results from this study.

KW - Cargo discharge time estimation

KW - Industry implementation

KW - Integrated logistics chain

KW - Short sea shipping

KW - Terminal operations

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U2 - 10.1007/978-3-030-31140-7_8

DO - 10.1007/978-3-030-31140-7_8

M3 - Article in proceeding

AN - SCOPUS:85075620585

SN - 9783030311391

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 122

EP - 135

BT - Computational Logistics - 10th International Conference, ICCL 2019, Proceedings

A2 - Paternina-Arboleda, Carlos

A2 - Voß, Stefan

PB - Springer

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Y2 - 30 September 2019 through 2 October 2019

ER -

Jia B, Rytter NGM, Reinhardt LB, Haulot G, Billesø MB. Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping. In Paternina-Arboleda C, Voß S, editors, Computational Logistics - 10th International Conference, ICCL 2019, Proceedings. Springer. 2019. p. 122-135. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11756). doi: 10.1007/978-3-030-31140-7_8

Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping

Abstract

Conference

Keywords

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PhD Project on Improving Eco-efficiency through Digitalisation and Optimisation in RoRo Shipping Industry

Cite this

Estimating Discharge Time of Cargo Units – A Case of Ro-Ro Shipping

Abstract

Conference

Keywords

Access to Document

AUB Link

Other files and links

Fingerprint

Projects

PhD Project on Improving Eco-efficiency through Digitalisation and Optimisation in RoRo Shipping Industry

Cite this