Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems

Ratnaji Vanga; Yousef Maknoon; Lorant A. Tavasszy; Sarah Gelper

doi:10.1109/WSC57314.2022.10015289

Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems

Ratnaji Vanga
, Yousef Maknoon
, Lorant A. Tavasszy
, Sarah Gelper

Transport and Planning

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

222 Downloads (Pure)

Abstract

Traffic congestion is uncertain and undesirable in logistics and leads to arrival uncertainty at downstream locations engendering disruptions. This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. Due to the recent advancements in cyber-physical systems, we propose an adaptive system that uses the real-time truck Estimated Time of Arrival (ETA) data to make informed decisions. We develop an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. We developed a simulation model of the adaptive system and reported the estimated benefits from our initial experiments.

Original language	English
Title of host publication	Proceedings of the 2022 Winter Simulation Conference, WSC 2022
Editors	B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
Publisher	IEEE
Pages	1593-1602
Number of pages	10
ISBN (Electronic)	9798350309713
DOIs	https://doi.org/10.1109/WSC57314.2022.10015289
Publication status	Published - 2022
Event	2022 Winter Simulation Conference, WSC 2022 - Guilin, China Duration: 11 Dec 2022 → 14 Dec 2022

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2022-December
ISSN (Print)	0891-7736

Conference

Conference	2022 Winter Simulation Conference, WSC 2022
Country/Territory	China
City	Guilin
Period	11/12/22 → 14/12/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1109/WSC57314.2022.10015289

Effect_of_Real-Time_Truck_Arrival_Information_on_the_Resilience_of_Slot_Management_SystemsFinal published version, 330 KB

Cite this

Vanga, R., Maknoon, Y., Tavasszy, L. A., & Gelper, S. (2022). Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems. In B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C. G. Corlu, L. H. Lee, E. P. Chew, T. Roeder, & P. Lendermann (Eds.), Proceedings of the 2022 Winter Simulation Conference, WSC 2022 (pp. 1593-1602). (Proceedings - Winter Simulation Conference; Vol. 2022-December). IEEE. https://doi.org/10.1109/WSC57314.2022.10015289

Vanga, Ratnaji ; Maknoon, Yousef ; Tavasszy, Lorant A. et al. / Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems. Proceedings of the 2022 Winter Simulation Conference, WSC 2022. editor / B. Feng ; G. Pedrielli ; Y. Peng ; S. Shashaani ; E. Song ; C.G. Corlu ; L.H. Lee ; E.P. Chew ; T. Roeder ; P. Lendermann. IEEE, 2022. pp. 1593-1602 (Proceedings - Winter Simulation Conference).

@inproceedings{774e0d99aa904051bc9907bf437fa7a4,

title = "Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems",

abstract = "Traffic congestion is uncertain and undesirable in logistics and leads to arrival uncertainty at downstream locations engendering disruptions. This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. Due to the recent advancements in cyber-physical systems, we propose an adaptive system that uses the real-time truck Estimated Time of Arrival (ETA) data to make informed decisions. We develop an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. We developed a simulation model of the adaptive system and reported the estimated benefits from our initial experiments. ",

author = "Ratnaji Vanga and Yousef Maknoon and Tavasszy, \{Lorant A.\} and Sarah Gelper",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2022 Winter Simulation Conference, WSC 2022 ; Conference date: 11-12-2022 Through 14-12-2022",

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doi = "10.1109/WSC57314.2022.10015289",

language = "English",

series = "Proceedings - Winter Simulation Conference",

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editor = "B. Feng and G. Pedrielli and Y. Peng and S. Shashaani and E. Song and C.G. Corlu and L.H. Lee and E.P. Chew and T. Roeder and P. Lendermann",

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Vanga, R, Maknoon, Y , Tavasszy, LA & Gelper, S 2022, Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems. in B Feng, G Pedrielli, Y Peng, S Shashaani, E Song, CG Corlu, LH Lee, EP Chew, T Roeder & P Lendermann (eds), Proceedings of the 2022 Winter Simulation Conference, WSC 2022. Proceedings - Winter Simulation Conference, vol. 2022-December, IEEE, pp. 1593-1602, 2022 Winter Simulation Conference, WSC 2022, Guilin, China, 11/12/22. https://doi.org/10.1109/WSC57314.2022.10015289

Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems. / Vanga, Ratnaji; Maknoon, Yousef ; Tavasszy, Lorant A. et al.
Proceedings of the 2022 Winter Simulation Conference, WSC 2022. ed. / B. Feng; G. Pedrielli; Y. Peng; S. Shashaani; E. Song; C.G. Corlu; L.H. Lee; E.P. Chew; T. Roeder; P. Lendermann. IEEE, 2022. p. 1593-1602 (Proceedings - Winter Simulation Conference; Vol. 2022-December).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Vanga, Ratnaji

AU - Maknoon, Yousef

AU - Tavasszy, Lorant A.

AU - Gelper, Sarah

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2022

Y1 - 2022

N2 - Traffic congestion is uncertain and undesirable in logistics and leads to arrival uncertainty at downstream locations engendering disruptions. This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. Due to the recent advancements in cyber-physical systems, we propose an adaptive system that uses the real-time truck Estimated Time of Arrival (ETA) data to make informed decisions. We develop an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. We developed a simulation model of the adaptive system and reported the estimated benefits from our initial experiments.

AB - Traffic congestion is uncertain and undesirable in logistics and leads to arrival uncertainty at downstream locations engendering disruptions. This paper considers a loading facility that uses Truck Appointment System (TAS) for slot management and faces incoming truck arrival uncertainty due to traffic congestion. Due to the recent advancements in cyber-physical systems, we propose an adaptive system that uses the real-time truck Estimated Time of Arrival (ETA) data to make informed decisions. We develop an integer mathematical model to represent the adaptive behavior that determines the optimal reschedules by minimizing the average truck waiting time. We developed a simulation model of the adaptive system and reported the estimated benefits from our initial experiments.

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A2 - Peng, Y.

A2 - Shashaani, S.

A2 - Song, E.

A2 - Corlu, C.G.

A2 - Lee, L.H.

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PB - IEEE

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ER -

Vanga R, Maknoon Y , Tavasszy LA, Gelper S. Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems. In Feng B, Pedrielli G, Peng Y, Shashaani S, Song E, Corlu CG, Lee LH, Chew EP, Roeder T, Lendermann P, editors, Proceedings of the 2022 Winter Simulation Conference, WSC 2022. IEEE. 2022. p. 1593-1602. (Proceedings - Winter Simulation Conference). doi: 10.1109/WSC57314.2022.10015289

Effect of Real-Time Truck Arrival Information on the Resilience of Slot Management Systems

Abstract

Publication series

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Bibliographical note

UN SDGs

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