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

Beizhen Jia; Niels Gorm Rytter; Line Reinhardt; Gauvain Haulot; Mads Bentzen Billesøe

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 Rytter, Line Reinhardt, Gauvain Haulot, Mads Bentzen Billesøe

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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 …

Originalsprog	Engelsk
Titel	Computational Logistics : 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings
Redaktører	Carlos Paternina-Arboleda, Stefan Voß
Antal sider	13
Forlag	Springer
Publikationsdato	30 sep. 2019
Sider	122-135
ISBN (Trykt)	978-3-030-31139-1
ISBN (Elektronisk)	978-3-030-31140-7
DOI	https://doi.org/10.1007/978-3-030-31140-7_8
Status	Udgivet - 30 sep. 2019
Begivenhed	10th International Conference on Computational Logistics - Universidad del Norte, Barranquilla, Colombia Varighed: 30 sep. 2019 → 2 okt. 2019 http://iccl2019.co/

Konference

Konference	10th International Conference on Computational Logistics
Lokation	Universidad del Norte
Land/Område	Colombia
By	Barranquilla
Periode	30/09/2019 → 02/10/2019
Internetadresse	http://iccl2019.co/

Navn	Lecture Notes in Computer Science
Nummer	11756
ISSN	0302-9743

Link til dokument

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

Estimating Discharging Time of Cargo Units A Case of Ro-Ro ShippingAccepteret manuskript, 519 KB

Citer dette

Jia, B., Rytter, N. G., Reinhardt, L., Haulot, G., & Billesøe, M. B. (2019). Estimating Discharge Time of Cargo Units: A Case of Ro-Ro Shipping. I C. Paternina-Arboleda, & S. Voß (red.), Computational Logistics: 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings (s. 122-135). Springer. https://doi.org/10.1007/978-3-030-31140-7_8

Jia, Beizhen ; Rytter, Niels Gorm ; Reinhardt, Line et al. / Estimating Discharge Time of Cargo Units : A Case of Ro-Ro Shipping. Computational Logistics: 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings. red. / Carlos Paternina-Arboleda ; Stefan Voß. Springer, 2019. s. 122-135 (Lecture Notes in Computer Science; Nr. 11756).

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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 I, Short sea shipping, Terminal operations",

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Jia, B, Rytter, NG, Reinhardt, L, Haulot, G & Billesøe, MB 2019, Estimating Discharge Time of Cargo Units: A Case of Ro-Ro Shipping. i C Paternina-Arboleda & S Voß (red), Computational Logistics: 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings. Springer, Lecture Notes in Computer Science, nr. 11756, s. 122-135, 10th International Conference on Computational Logistics, 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; Reinhardt, Line et al.
Computational Logistics: 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings. red. / Carlos Paternina-Arboleda; Stefan Voß. Springer, 2019. s. 122-135 (Lecture Notes in Computer Science; Nr. 11756).

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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AU - Jia, Beizhen

AU - Rytter, Niels Gorm

AU - Reinhardt, Line

AU - Haulot, Gauvain

AU - Billesøe, Mads Bentzen

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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.

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Jia B, Rytter NG, Reinhardt L, Haulot G, Billesøe MB. Estimating Discharge Time of Cargo Units: A Case of Ro-Ro Shipping. I Paternina-Arboleda C, Voß S, red., Computational Logistics: 10th International Conference, ICCL 2019, Barranquilla, Colombia, September 30 – October 2, 2019, Proceedings. Springer. 2019. s. 122-135. (Lecture Notes in Computer Science; Nr. 11756). doi: 10.1007/978-3-030-31140-7_8