A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions

Mauro Vallati; Lukáš Chrpa

doi:10.1007/978-3-030-64984-5_7

A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In order to keep roads in acceptable condition, and to perform maintenance of essential infrastructure, roadworks are required. Due to the increasing traffic volumes and the increasing urbanisation, road agencies are currently facing the problem of effective planning frequent –and usually concurrent– roadworks in the controlled region. However, there is a lack of techniques that can support traffic authorities in this task. In fact, traffic authorities have usually to rely on human experts (and their intuition) to decide how to schedule and perform roadworks. In this paper, we introduce a Mixed-Integer Programming approach that can be used by traffic authorities to plan a set of required roadworks, over a period of time, in a large urban region, by specifying constraints to be satisfied and suitable quality metrics.

Original language	English
Title of host publication	Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence
Subtitle of host publication	(AI2020)
Editors	Marcus Gallagher, Nour Moustafa, Erandi Lakshika
Place of Publication	Cham
Publisher	Springer Nature Switzerland AG
Pages	82-93
Number of pages	12
Volume	12576 LNCS/LNAI
ISBN (Electronic)	9783030649845
ISBN (Print)	9783030649838
DOIs	https://doi.org/10.1007/978-3-030-64984-5_7
Publication status	Published - 27 Nov 2020
Event	33rd Australasian Joint Conference on Artificial Intelligence - Virtual conference due to COVID-19 Duration: 29 Nov 2020 → 30 Nov 2020 Conference number: 33 http://www.ajcai2020.net/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Nature Switzerland AG
Volume	12576 LNCS/LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	33rd Australasian Joint Conference on Artificial Intelligence
Abbreviated title	AI2020
Period	29/11/20 → 30/11/20
Internet address	http://www.ajcai2020.net/

UN SDGs

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

Access to Document

10.1007/978-3-030-64984-5_7Licence: Unspecified

MIP___AJCAI_20Accepted author manuscript, 596 KBLicence: Unspecified

Cite this

Vallati, M., & Chrpa, L. (2020). A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. In M. Gallagher, N. Moustafa, & E. Lakshika (Eds.), Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence: (AI2020) (Vol. 12576 LNCS/LNAI, pp. 82-93). (Lecture Notes in Computer Science; Vol. 12576 LNCS/LNAI). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-64984-5_7

Vallati, Mauro ; Chrpa, Lukáš. / A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence: (AI2020). editor / Marcus Gallagher ; Nour Moustafa ; Erandi Lakshika. Vol. 12576 LNCS/LNAI Cham : Springer Nature Switzerland AG, 2020. pp. 82-93 (Lecture Notes in Computer Science).

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title = "A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions",

abstract = "In order to keep roads in acceptable condition, and to perform maintenance of essential infrastructure, roadworks are required. Due to the increasing traffic volumes and the increasing urbanisation, road agencies are currently facing the problem of effective planning frequent –and usually concurrent– roadworks in the controlled region. However, there is a lack of techniques that can support traffic authorities in this task. In fact, traffic authorities have usually to rely on human experts (and their intuition) to decide how to schedule and perform roadworks. In this paper, we introduce a Mixed-Integer Programming approach that can be used by traffic authorities to plan a set of required roadworks, over a period of time, in a large urban region, by specifying constraints to be satisfied and suitable quality metrics.",

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booktitle = "Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence",

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Vallati, M & Chrpa, L 2020, A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. in M Gallagher, N Moustafa & E Lakshika (eds), Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence: (AI2020). vol. 12576 LNCS/LNAI, Lecture Notes in Computer Science, vol. 12576 LNCS/LNAI, Springer Nature Switzerland AG, Cham, pp. 82-93, 33rd Australasian Joint Conference on Artificial Intelligence, 29/11/20. https://doi.org/10.1007/978-3-030-64984-5_7

A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. / Vallati, Mauro; Chrpa, Lukáš.

Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence: (AI2020). ed. / Marcus Gallagher; Nour Moustafa; Erandi Lakshika. Vol. 12576 LNCS/LNAI Cham : Springer Nature Switzerland AG, 2020. p. 82-93 (Lecture Notes in Computer Science; Vol. 12576 LNCS/LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - In order to keep roads in acceptable condition, and to perform maintenance of essential infrastructure, roadworks are required. Due to the increasing traffic volumes and the increasing urbanisation, road agencies are currently facing the problem of effective planning frequent –and usually concurrent– roadworks in the controlled region. However, there is a lack of techniques that can support traffic authorities in this task. In fact, traffic authorities have usually to rely on human experts (and their intuition) to decide how to schedule and perform roadworks. In this paper, we introduce a Mixed-Integer Programming approach that can be used by traffic authorities to plan a set of required roadworks, over a period of time, in a large urban region, by specifying constraints to be satisfied and suitable quality metrics.

AB - In order to keep roads in acceptable condition, and to perform maintenance of essential infrastructure, roadworks are required. Due to the increasing traffic volumes and the increasing urbanisation, road agencies are currently facing the problem of effective planning frequent –and usually concurrent– roadworks in the controlled region. However, there is a lack of techniques that can support traffic authorities in this task. In fact, traffic authorities have usually to rely on human experts (and their intuition) to decide how to schedule and perform roadworks. In this paper, we introduce a Mixed-Integer Programming approach that can be used by traffic authorities to plan a set of required roadworks, over a period of time, in a large urban region, by specifying constraints to be satisfied and suitable quality metrics.

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Vallati M, Chrpa L. A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. In Gallagher M, Moustafa N, Lakshika E, editors, Proceedings of the 33rd Australasian Joint Conference on Artificial Intelligence: (AI2020). Vol. 12576 LNCS/LNAI. Cham: Springer Nature Switzerland AG. 2020. p. 82-93. (Lecture Notes in Computer Science). Epub 2020 Nov 27. doi: 10.1007/978-3-030-64984-5_7

A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions

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