Skip to main content
Springer Nature Link
Log in

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

  • Conference paper
  • First Online:
AI 2020: Advances in Artificial Intelligence (AI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12576))

Included in the following conference series:

  • 1415 Accesses

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    United Nations - https://rb.gy/nsqvcw.

  2. 2.

    https://bbc.in/2C6l1mu.

  3. 3.

    https://github.com/chuffed/chuffed.

References

  1. CSPLib language minizinc. http://www.csplib.org/Languages/MiniZinc

  2. Bixby, E.R., Fenelon, M., Gu, Z., Rothberg, E., Wunderling, R.: MIP: theory and practice — closing the gap. In: Powell, M.J.D., Scholtes, S. (eds.) CSMO 1999. ITIFIP, vol. 46, pp. 19–49. Springer, Boston (2000). https://doi.org/10.1007/978-0-387-35514-6_2

    Chapter  MATH  Google Scholar 

  3. Burningham, S., Stankevich, N.: Why road maintenance is important and how to get it done (2005)

    Google Scholar 

  4. Forrest, J., Lougee-Heimer, R.: CBC user guide. In: Emerging Theory, Methods, and Applications, pp. 257–277. INFORMS (2005)

    Google Scholar 

  5. Garrido-Jurado, S., Muñoz-Salinas, R., Madrid-Cuevas, F., Medina-Carnicer, R.: Generation of fiducial marker dictionaries using mixed integer linear programming. Pattern Recogn. 51, 481–491 (2016)

    Article  Google Scholar 

  6. Huerne, H.t., Berkum, E.v., Hermelink, W.: A multi objective framework to optimise planning of road works. In: 5th Eurasphalt and Eurobitume Congress (2012)

    Google Scholar 

  7. Hussain, R.S., Ruikar, K., Enoch, M.P., Brien, N., Gartside, D.: Process mapping for road works planning and coordination. Built Environ. Proj. Asset Manag. 7(2), 157–172 (2017)

    Article  Google Scholar 

  8. Ghallab, M., Nau, D., Traverso, P.: Automated Planning Theory and Practice. Elsevier, San Francisco (2004)

    MATH  Google Scholar 

  9. Nethercote, N., Stuckey, P.J., Becket, R., Brand, S., Duck, G.J., Tack, G.: MiniZinc: towards a standard CP modelling language. In: Bessière, C. (ed.) CP 2007. LNCS, vol. 4741, pp. 529–543. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74970-7_38

    Chapter  Google Scholar 

  10. Paquay, C., Schyns, M., Limbourg, S.: A mixed integer programming formulation for the three-dimensional bin packing problem deriving from an air cargo application. Int. Trans. Oper. Res. 23(1–2), 187–213 (2016)

    Article  MathSciNet  Google Scholar 

  11. Scala, E., Haslum, P., Thiébaux, S., Ramírez, M.: Interval-based relaxation for general numeric planning. In: Proceedings of ECAI, pp. 655–663 (2016)

    Google Scholar 

  12. Schulte, C., Stuckey, P.J.: Efficient constraint propagation engines. ACM Trans. Program. Lang. Syst. (TOPLAS) 31(1), 2 (2008)

    Article  Google Scholar 

  13. Stuckey, P.J., Feydy, T., Schutt, A., Tack, G., Fischer, J.: The MiniZinc challenge 2008–2013. AI Mag. 35(2), 55–60 (2014)

    Article  Google Scholar 

  14. Valicka, C.G., et al.: Mixed-integer programming models for optimal constellation scheduling given cloud cover uncertainty. Eur. J. Oper. Res. 275(2), 431–445 (2018)

    Article  MathSciNet  Google Scholar 

  15. Vallati, M., Chrpa, L., Kitchin, D.: How to plan roadworks in urban regions? A principled approach based on AI planning. In: Rodrigues, J.M.F., et al. (eds.) ICCS 2019. LNCS, vol. 11540, pp. 453–460. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22750-0_37

    Chapter  Google Scholar 

  16. Ye, Y., Grossmann, I.E., Pinto, J.M.: Mixed-integer nonlinear programming models for optimal design of reliable chemical plants. Comput. Chem. Eng. 116, 3–16 (2018)

    Article  Google Scholar 

Download references

Acknowledgement

L. Chrpa was partially funded by the Czech Science Foundation (project no. 18-07252S). M. Vallati was partially supported by the EPSRC grant EP/R51343X/1 (AI4ME).

Author information

Authors and Affiliations

  1. University of Huddersfield, Huddersfield, UK

    Mauro Vallati

  2. Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic

    Lukáš Chrpa

Authors
  1. Mauro Vallati
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lukáš Chrpa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mauro Vallati .

Editor information

Editors and Affiliations

  1. School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, QLD, Australia

    Marcus Gallagher

  2. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

    Nour Moustafa

  3. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

    Erandi Lakshika

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vallati, M., Chrpa, L. (2020). A Mixed-Integer Programming Approach for Scheduling Roadworks in Urban Regions. In: Gallagher, M., Moustafa, N., Lakshika, E. (eds) AI 2020: Advances in Artificial Intelligence. AI 2020. Lecture Notes in Computer Science(), vol 12576. Springer, Cham. https://doi.org/10.1007/978-3-030-64984-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-64984-5_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64983-8

  • Online ISBN: 978-3-030-64984-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation