Skip to main content
SpringerLink
Log in
Book cover

International Conference on Innovative Techniques and Applications of Artificial Intelligence

SGAI 2014: Research and Development in Intelligent Systems XXXI pp 171–177Cite as

De-risking Fleet Replacement Decisions

  • Conference paper
  • First Online:

  • 510 Accesses

Abstract

This paper outlines the different modelling approaches for realizing sustainable operations of asset replacement. We study the fleet portfolio management problem that could be faced by a firm deciding ahead which vehicles to choose for its fleet. In particular it suggests a model that enables generating a plan of vehicle replacement actions with cost minimization and risk exposure simulation. It proposes to use conditional value at risk (CVaR) to account for uncertainty in the decision process, and to use clusters modelling to align the generated plan with vehicle utilization.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Ansaripoor, A.H., Oliveira, F., Liret, A.: An improved decision support system for sustainable fleet replacement. J. Oper. Res. Soc. 237(2), 701–712 (2014)

    Article  MathSciNet  Google Scholar 

  2. Hartman, J.C.: The parallel replacement problem with demand and capital budgeting constraints. Naval Res. Logistics (NRL). 47(1), 40–56 (2000)

    Article  MATH  Google Scholar 

  3. Hartman, J.C.: A note on “a strategy for optimal equipment replacement”. Prod. Planning Control 16(7), 733–739 (2005)

    Article  Google Scholar 

  4. Karabakal, N., Lohmann, J.R., Bean, J.C.: Parallel replacement under capital rationing constraints. Manag. Sci. 40(3), 305–319 (1994)

    Article  MATH  Google Scholar 

  5. Shapiro, A.: On a time consistency concept in risk averse multistage stochastic programming. Oper. Res. Lett. 37(3), 143–147 (2009)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. British Telecom, Paris, France

    Anne Liret

  2. ESSEC Business School, Singapore, Singapore

    Amir H. Ansaripoor & Fernando S. Oliveira

Authors
  1. Anne Liret
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amir H. Ansaripoor
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fernando S. Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anne Liret .

Editor information

Editors and Affiliations

  1. University of Portsmouth, Portsmouth, United Kingdom

    Max Bramer

  2. School of Computing, Eng & Mathematics, University of Brighton, Brighton, West Sussex, United Kingdom

    Miltos Petridis

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Liret, A., Ansaripoor, A.H., Oliveira, F.S. (2014). De-risking Fleet Replacement Decisions. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXXI. SGAI 2014. Springer, Cham. https://doi.org/10.1007/978-3-319-12069-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12069-0_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12068-3

  • Online ISBN: 978-3-319-12069-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation