Skip to main content
SpringerLink
Log in

Online and Offline Container Purchasing and Repositioning Problem

  • Conference paper
  • First Online:
Computational Logistics (ICCL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9855))

Included in the following conference series:

  • 1752 Accesses

Abstract

We study the management of containers in a logistic chain between a supplier and a manufacturer in a ramp-up scenario where the demand is stochastic and expected to increase. This paper extends our previous study with deterministic demand. We consider a periodic review system with T periods of R time steps. The supplier sends full containers at every step and receives empty containers every period. We consider positive lead times. To face demand increase, the manufacturer can purchase reusable containers at a setup cost while the supplier can buy single-use disposables. Using a dynamic programming framework, we develop an online exact algorithm and an offline heuristic.

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

Access this chapter

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

References

  1. Jami, N., Schroeder, M., Küfer, K.: A model and polynomial algorithm for purchasing and repositioning containers. In: Management and Control of Production and Logistics (upcoming), vol. 7 (accepted 2016)

    Google Scholar 

  2. Janakiraman, G., Muckstadt, J.A.: Periodic review inventory control with lost sales and fractional lead times. Cornell University, School of Operations Research and Industrial Engineering (2004)

    Google Scholar 

  3. Halman, N., Klabjan, D., Mostagir, M., Orlin, J., Simchi-Levi, D.: A fully polynomial-time approximation scheme for single-item stochastic inventory control with discrete demand. Math. Oper. Res. 34(3), 674–685 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  4. Murota, K.: Discrete Convex Analysis. SIAM, Philadelphia (2003)

    Book  MATH  Google Scholar 

  5. Zipkin, P.: On the structure of lost-sales inventory models. Oper. Res. 56(4), 937–944 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  6. Simchi-Levi, D., Chen, X., Bramel, J.: The Logic of Logistics: Theory, Algorithms, and Applications for Logistics Management. Springer Science & Business Media, New York (2013)

    MATH  Google Scholar 

  7. Chen, W., Dawande, M., Janakiraman, G.: Fixed-dimensional stochastic dynamic programs: an approximation scheme and an inventory application. Oper. Res. 62(1), 81–103 (2014)

    Article  MATH  MathSciNet  Google Scholar 

  8. Wagner, H.M., Whitin, T.M.: Dynamic version of the economic lot size model. Manag. Sci. 5(1), 89–96 (1958)

    Article  MATH  MathSciNet  Google Scholar 

  9. Bookbinder, J.H., Tan, J.Y.: Strategies for the probabilistic lot-sizing problem with service-level constraints. Manag. Sci. 34(9), 1096–1108 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  10. Levi, R., Shi, C.: Approximation algorithms for the stochastic lot-sizing problem with order lead times. Oper. Res. 61(3), 593–602 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  11. Vargas, V.: An optimal solution for the stochastic version of the Wagner-Whitin dynamic lot-size model. Eur. J. Oper. Res. 198(2), 447–451 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  12. Özen, U., Doğru, M.K., Tarim, S.A.: Static-dynamic uncertainty strategy for a single-item stochastic inventory control problem. Omega 40(3), 348–357 (2012)

    Article  Google Scholar 

  13. Erera, A.L., Morales, J.C., Savelsbergh, M.: Global intermodal tank container management for the chemical industry. Transp. Res. Part E Logistics Transp. Rev. 41(6), 551–566 (2005)

    Article  Google Scholar 

  14. Erera, A.L., Morales, J.C., Savelsbergh, M.: Robust optimization for empty repositioning problems. Oper. Res. 57(2), 468–483 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  15. Li, J.A., Leung, S.C., Wu, Y., Liu, K.: Allocation of empty containers between multi-ports. Eur. J. Oper. Res. 182(1), 400–412 (2007)

    Article  MATH  Google Scholar 

  16. Lam, S.W., Lee, L.H., Tang, L.C.: An approximate dynamic programming approach for the empty container allocation problem. Transp. Res. Part C Emerg. Technol. 15(4), 265–277 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Fraunhofer Institute for Industrial Mathematics (ITWM), 67663, Kaiserslautern, Germany

    Neil Jami, Michael Schröder & Karl-Heinz Küfer

Authors
  1. Neil Jami
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Schröder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Karl-Heinz Küfer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Neil Jami .

Editor information

Editors and Affiliations

  1. Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal

    Ana Paias

  2. University of Vienna , Vienna, Austria

    Mario Ruthmair

  3. University of Hamburg , Hamburg, Hamburg, Germany

    Stefan Voß

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Jami, N., Schröder, M., Küfer, KH. (2016). Online and Offline Container Purchasing and Repositioning Problem. In: Paias, A., Ruthmair, M., Voß, S. (eds) Computational Logistics. ICCL 2016. Lecture Notes in Computer Science(), vol 9855. Springer, Cham. https://doi.org/10.1007/978-3-319-44896-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-44896-1_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44895-4

  • Online ISBN: 978-3-319-44896-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation