Skip to main content
Log in

A new approach to the Container Positioning Problem

  • Published:
Flexible Services and Manufacturing Journal Aims and scope Submit manuscript

Abstract

In this paper the Container Positioning Problem is revisited. This problem arises at busy container terminals and requires one to minimize the use of block cranes in handling the containers that must wait at the terminal until their next means of transportation. We propose a new Mixed Integer Programming model that not only improves on earlier attempts at this problem, but also better reflects reality. In particular, the proposed model adopts a preference to reshuffle containers in line with a just-in-time concept, as it is assumed that data is more accurate the closer to a container’s scheduled departure the time is. Other important improvements include a reduction in the model size, and the ability of the model to consider containers initially at the terminal. In addition, we describe several classes of valid inequalities for this new formulation and present a rolling horizon based heuristic for solving larger instances of the problem. We show that this new formulation drastically outperforms previous attempts at the problem through a direct comparison on instances available in the literature. Furthermore, we also show that the rolling horizon based heuristic can further reduce the solution time on the larger of these instances as well as find acceptable solutions to much bigger, artificially generated, instances.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Ahmt J, Sigtenbjerggaard JS (2010) A new approach to the Container Positioning Problem. Master’s thesis, Technical University of Denmark

  • Bierwirth C, Meisel F (2010) A survey of berth allocation and quay crane scheduling problems in container terminals. Eur J Oper Res 202(3):615–627

    Article  MathSciNet  MATH  Google Scholar 

  • Bish E (2003) A multiple-crane-constrained scheduling problem in a container terminal. Eur J Oper Res 144:83–107

    Article  MathSciNet  MATH  Google Scholar 

  • Bish EK, Leong T-Y, Li C-L, Ng JWC, Simchi-Levi D (2001) Analysis of a new vehicle scheduling and location problem. Nav Res Logist 48(5):363–385

    Article  MathSciNet  MATH  Google Scholar 

  • Bish EK, Chen FY, Leong YT, Nelson BL, Ng JWC, Simchi-Levi D (2005) Dispatching vehicles in a mega container terminal. OR Spectr 27(4):491–506

    Article  MATH  Google Scholar 

  • Cao B, Uebe G (1993) An algorithm for solving capacitated multicommodity p-median transportation problems. J Oper Res Soc 44(3):259–269

    Article  MATH  Google Scholar 

  • Chen L, Bostel N, Dejax P, Cai J, Xi L (2006) A tabu search algorithm for the integrated scheduling problem of container handling systems in a maritime terminal. Eur J Oper Res 181:40–58

    Article  MathSciNet  MATH  Google Scholar 

  • Cordeau J-F, Gaudioso M, Laporte G, Moccia L (2007) The service allocation problem at Gioia Tauro maritime terminal. Eur J Oper Res 176:1167–1184

    Article  MATH  Google Scholar 

  • Dekker R, Voogd P, Asperen E (2006) Advanced methods for container stacking. OR Spectr 28:563–586

    Article  MATH  Google Scholar 

  • Delgado A, Jensen RM, Janstrup K, Roser TH, Andersen KH (2012) A constraint programming model for fast optimal stowage of container vessel bays. Eur J Oper Res 220(1):251–261

    Article  MathSciNet  MATH  Google Scholar 

  • Exposito-Izquierdo C, Melian-Batista B, Moreno-Vega M (2012) Pre-marshalling problem: heuristic solution method and instances generator. Expert Syst Appl 39(9):8337–8349

    Article  Google Scholar 

  • Forster F, Bortfeldt A (2012) A tree search procedure for the container relocation problem. Comput Oper Res 39(2):299–309

    Article  MathSciNet  MATH  Google Scholar 

  • Kang J, Oh M-S, Ahn EY, Ryu KR, Kim KH (2006a) Planning for intra-block remarshaling in a container terminal. In: Moonis A, Richard D (eds) Advances in applied artificial intelligence. Lecture Notes in Computer Science, vol 4031. Springer, Berlin, pp 1211–1220

  • Kang J, Ryu KR, Kim KH (2006b) Determination of storage locations for incoming containers of uncertain weight. Adv Appl Artif Intell 4031:1159–1168

    Article  Google Scholar 

  • Kim KH, Hong G-P (2006) A heuristic rule for relocating blocks. Comput Oper Res 33:940–954

    Article  MATH  Google Scholar 

  • Kim KH, Kim KY (1999) Routing straddle carriers for the loading operation of containers using a beam search algorithm. Comput Ind Eng 36:109–136

    Article  Google Scholar 

  • Kim KH, Lee J-S (2006) Satisfying constraints for locating export containers in port container terminals. Comput Sci Its Appl 3982:564–573

    Google Scholar 

  • Kim KH, Park KT (2003) A note on a dynamic space-allocation method for outbound containers. Eur J Oper Res 148:92–101

    Article  MATH  Google Scholar 

  • Kim K, Park Y, Ryu K (2000) Deriving decision rules to locate export containers in container yards. Eur J Oper Res 124:89–101

    Article  MATH  Google Scholar 

  • Kozan E, Preston P (2006) Mathematical modeling of container transfers and storage locations at seaport terminals. Eur J Oper Res 28:519–537

    MATH  Google Scholar 

  • Lee Y, Chao S-L (2009) A neighborhood search heuristic for pre-marshalling export containers. Eur J Oper Res 196(2):468–475

    Article  MathSciNet  Google Scholar 

  • Lee Y, Hsu N-Y (2007) An optimization model for the container pre-marshalling problem. Comput Oper Res 34:3295–3313

    Article  MATH  Google Scholar 

  • Lee LH, Chew EP, Tan KC, Han Y (2006) An optimization model for storage yard management in transshipment hubs. OR Spectr 28:539–561

    Article  MATH  Google Scholar 

  • Levinson M (2006) The box: how the shipping container made the world smaller and the world economy bigger. Princeton University Press, Princeton

    Google Scholar 

  • Paolucci M, Recagno V, Sacone S (1998) Designing container yard management systems. In: Proceedings of the international conference on computer aided design, manufacturing and operation in the railway and other advanced mass transit systems, pp 351–360

  • Park K, Park T, Ryu KR (2013) Planning for selective remarshaling in an automated container terminal using coevolutionary algorithms. Int J Ind Eng 20(1–2):176

    Google Scholar 

  • Phillips A (2009) Optimisation models and methods for the Container Positioning Problem in port terminals. Technical report, University of Auckland

  • Preston P, Kozan E (2001) An approach to determine storage location of containers at seaport terminals. Comput Oper Res 28:983–995

    Article  MATH  Google Scholar 

  • Sibbesen LK (2008) Mathematical models and heuristic solutions for Container Positioning Problems in port terminals. PhD thesis, Technical University of Denmark

  • Stahlbock R, Voß S (2008) Operations research at container terminals: a literature update. OR Spectr 30:1–52

    Article  MathSciNet  MATH  Google Scholar 

  • Steenken D, Voß S, Stahlbock R (2004) Container terminal operation and operations research—a classification and literature review. OR Spectr 26:3–49

    Article  MATH  Google Scholar 

  • Taleb-Ibrahimi M, de Castilho B, Daganzo CF (1993) Storage space vs handling work in container terminals. Transp Res Part B Methodol 27:13–32

    Article  Google Scholar 

  • Wu Y, Luo J, Zhang D, Dong M (2013) An integrated programming model for storage management and vehicle scheduling at container terminals. Res Transp Econ 42(1):13–27

    Article  Google Scholar 

  • Yu M, Qi X (2013) Storage space allocation models for inbound containers in an automatic container terminal. Eur J Oper Res 226(1):32–45

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Antony Phillips (University of Auckland) for providing us with his thesis (Phillips 2009), Python code and all test cases. In addition, the authors would also like to thank Finn Nørgaard and Carsten Gitter from InPort. Finn and Carsten were helpful with providing information to get a better understanding of the real-life challenges in the CPP. This research has been partially supported by the European Union Seventh Framework Programme (FP7-PEOPLE-2009-IRSES) under Grant Agreement Number 246647 and by the New Zealand Government as part of the OptALI project.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jesper Larsen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ahmt, J., Sigtenbjerggaard, J.S., Lusby, R.M. et al. A new approach to the Container Positioning Problem. Flex Serv Manuf J 28, 617–643 (2016). https://doi.org/10.1007/s10696-015-9228-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10696-015-9228-0

Keywords

Navigation