Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach

Ulrike Ritzinger; Bin Hu; Martin Reinthaler

doi:10.1007/978-3-031-82949-9_12

Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach

Ulrike Ritzinger
, Bin Hu
, Martin Reinthaler

Integrated Energy Systems

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

Abstract

Connected and automated vehicles will soon disrupt the logistics and freight transport system. While AI advancements offer potential solutions, challenges like high development costs, safety requirements, and legal issues persist. This paper presents an optimization algorithm for scheduling automated guided vehicles (AGV) in yard logistics. In the problem setting, a fleet of AGVs needs to fulfill orders in an industry compound. The problem is modeled as a time-dependent pickup and delivery problem with time windows and solved with a large neighborhood search approach with destroy and repair neighborhoods and integrated conflict detection.
Computational experiments show that the algorithm is able to handle instances with up to 100 orders over 8 h and a fleet of up to four AGVs. Furthermore, they show the potential and scalability of integrating an optimization algorithm with an effective fleet management system in such a logistics system.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2024
Subtitle of host publication	EUROCAST 2024
Editors	Alexis Quesada-Arencibia, Michael Affenzeller, Roberto Moreno-Diaz
Publisher	Springer Nature
Pages	131-139
Volume	15172
ISBN (Electronic)	978-3-031-82949-9
ISBN (Print)	978-3-031-82951-2
DOIs	https://doi.org/10.1007/978-3-031-82949-9_12
Publication status	Published - 24 Apr 2025
Event	EUROCAST 2024: 19th International Conference on Computer Aided Systems Theory - Museo Elder, Las Palmas, Spain Duration: 25 Feb 2024 → 1 Mar 2024 Conference number: 19 https://eurocast2024.fulp.ulpgc.es/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Nature
Volume	15172
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	EUROCAST 2024
Abbreviated title	EUROCAST 2024
Country/Territory	Spain
City	Las Palmas
Period	25/02/24 → 1/03/24
Internet address	https://eurocast2024.fulp.ulpgc.es/

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Research Field

Transport Optimisation and Energy Logistics

Keywords

Automated Guided Vehicles
Yard Logistics
Time-dependent Travel Times
Large Neighborhood Search

Access to Document

10.1007/978-3-031-82949-9_12

Cite this

Ritzinger, U., Hu, B., & Reinthaler, M. (2025). Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach. In A. Quesada-Arencibia, M. Affenzeller, & R. Moreno-Diaz (Eds.), Computer Aided Systems Theory – EUROCAST 2024: EUROCAST 2024 (Vol. 15172, pp. 131-139). (Lecture Notes in Computer Science; Vol. 15172). Springer Nature. https://doi.org/10.1007/978-3-031-82949-9_12

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abstract = "Connected and automated vehicles will soon disrupt the logistics and freight transport system. While AI advancements offer potential solutions, challenges like high development costs, safety requirements, and legal issues persist. This paper presents an optimization algorithm for scheduling automated guided vehicles (AGV) in yard logistics. In the problem setting, a fleet of AGVs needs to fulfill orders in an industry compound. The problem is modeled as a time-dependent pickup and delivery problem with time windows and solved with a large neighborhood search approach with destroy and repair neighborhoods and integrated conflict detection. Computational experiments show that the algorithm is able to handle instances with up to 100 orders over 8 h and a fleet of up to four AGVs. Furthermore, they show the potential and scalability of integrating an optimization algorithm with an effective fleet management system in such a logistics system.",

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author = "Ulrike Ritzinger and Bin Hu and Martin Reinthaler",

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doi = "10.1007/978-3-031-82949-9\_12",

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booktitle = "Computer Aided Systems Theory – EUROCAST 2024",

address = "Switzerland",

note = "EUROCAST 2024 : 19th International Conference on Computer Aided Systems Theory, EUROCAST 2024 ; Conference date: 25-02-2024 Through 01-03-2024",

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Ritzinger, U , Hu, B & Reinthaler, M 2025, Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach. in A Quesada-Arencibia, M Affenzeller & R Moreno-Diaz (eds), Computer Aided Systems Theory – EUROCAST 2024: EUROCAST 2024. vol. 15172, Lecture Notes in Computer Science, vol. 15172, Springer Nature, pp. 131-139, EUROCAST 2024, Las Palmas, Spain, 25/02/24. https://doi.org/10.1007/978-3-031-82949-9_12

Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach. / Ritzinger, Ulrike ; Hu, Bin; Reinthaler, Martin.
Computer Aided Systems Theory – EUROCAST 2024: EUROCAST 2024. ed. / Alexis Quesada-Arencibia; Michael Affenzeller; Roberto Moreno-Diaz. Vol. 15172 Springer Nature, 2025. p. 131-139 (Lecture Notes in Computer Science; Vol. 15172).

Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

TY - GEN

T1 - Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach

AU - Ritzinger, Ulrike

AU - Hu, Bin

AU - Reinthaler, Martin

N1 - Conference code: 19

PY - 2025/4/24

Y1 - 2025/4/24

N2 - Connected and automated vehicles will soon disrupt the logistics and freight transport system. While AI advancements offer potential solutions, challenges like high development costs, safety requirements, and legal issues persist. This paper presents an optimization algorithm for scheduling automated guided vehicles (AGV) in yard logistics. In the problem setting, a fleet of AGVs needs to fulfill orders in an industry compound. The problem is modeled as a time-dependent pickup and delivery problem with time windows and solved with a large neighborhood search approach with destroy and repair neighborhoods and integrated conflict detection. Computational experiments show that the algorithm is able to handle instances with up to 100 orders over 8 h and a fleet of up to four AGVs. Furthermore, they show the potential and scalability of integrating an optimization algorithm with an effective fleet management system in such a logistics system.

AB - Connected and automated vehicles will soon disrupt the logistics and freight transport system. While AI advancements offer potential solutions, challenges like high development costs, safety requirements, and legal issues persist. This paper presents an optimization algorithm for scheduling automated guided vehicles (AGV) in yard logistics. In the problem setting, a fleet of AGVs needs to fulfill orders in an industry compound. The problem is modeled as a time-dependent pickup and delivery problem with time windows and solved with a large neighborhood search approach with destroy and repair neighborhoods and integrated conflict detection. Computational experiments show that the algorithm is able to handle instances with up to 100 orders over 8 h and a fleet of up to four AGVs. Furthermore, they show the potential and scalability of integrating an optimization algorithm with an effective fleet management system in such a logistics system.

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KW - Yard Logistics

KW - Time-dependent Travel Times

KW - Large Neighborhood Search

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M3 - Conference Proceedings with Oral Presentation

SN - 978-3-031-82951-2

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EP - 139

BT - Computer Aided Systems Theory – EUROCAST 2024

A2 - Quesada-Arencibia, Alexis

A2 - Affenzeller, Michael

A2 - Moreno-Diaz, Roberto

PB - Springer Nature

T2 - EUROCAST 2024

Y2 - 25 February 2024 through 1 March 2024

ER -

Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach

Abstract

Publication series

Conference

UN SDGs

Research Field

Keywords

Access to Document

Other files and links

Fingerprint

On-demand Automated Guided Vehicles in Yard Logistics

Cite this

Automated Guided Vehicles in Yard Logistics: A Time-Dependent Approach

Abstract

Publication series

Conference

UN SDGs

Research Field

Keywords

Access to Document

Other files and links

Fingerprint

Activities

On-demand Automated Guided Vehicles in Yard Logistics

Cite this