Skip to main content
SpringerLink
Log in

Maritime Container Terminal Problems

  • Living reference work entry
  • First Online:
Handbook of Heuristics

Abstract

Maritime container terminals are essential infrastructures in global supply chains. Their high management complexity and heterogeneous processes make them an interesting field to apply heuristics. A brief overview of the main optimization problems found at maritime container terminals and a review of the way they are related to each other are firstly introduced. In order to solve these problems, several heuristics are presented and analyzed. The computational results reveal that they are suitable to be applied in practical scenarios due to the fact that they provide high-quality solutions in short computational times.

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Angeloudis P, Bell MGH (2010) An uncertainty-aware AGV assignment algorithm for automated container terminals. Transp Res E Logist Transp Rev 46(3):354–366

    Article  Google Scholar 

  2. Bierwirth C, Meisel F (2009) A fast heuristic for quay crane scheduling with interference constraints. J Sched 12(4):345–360

    Article  MathSciNet  MATH  Google Scholar 

  3. 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 

  4. 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 

  5. Briskorn D, Drexl A, Hartmann S (2006) Inventory-based dispatching of automated guided vehicles on container terminals. OR Spectr 28(4):611–630

    Article  MATH  Google Scholar 

  6. Caserta M, Schwarze S, VoßS (2011) Container rehandling at maritime container terminals. In: Böse JW (ed) Handbook of terminal planning. Volume 49 of operations research/computer science interfaces series. Springer, New York, pp 247–269

    Google Scholar 

  7. Caserta M, Schwarze S, VoßS (2012) A mathematical formulation and complexity considerations for the blocks relocation problem. Eur J Oper Res 219(1):96–104

    Google Scholar 

  8. Chen G, Govindan K, Yang Z (2013) Managing truck arrivals with time windows to alleviate gate congestion at container terminals. Int J Prod Econ 141(1):179–188

    Article  Google Scholar 

  9. Cordeau JF, Laporte G, Legato P, Moccia L (2005) Models and tabu search heuristics for the berth-allocation problem. Transp Sci 39(4):526–538

    Article  Google Scholar 

  10. Cordeau JF, Gaudioso M, Laporte G, Moccia L (2007) The service allocation problem at the Gioia Tauro maritime terminal. Eur J Oper Res 176(2):1167–1184

    Article  MATH  Google Scholar 

  11. Expósito-Izquierdo C, Melián-Batista B, Moreno-Vega JM (2012) Pre-marshalling problem: heuristic solution method and instances generator. Expert Syst Appl 39(9):8337–8349

    Article  Google Scholar 

  12. Expósito-Izquierdo C, González-Velarde JL, Melián-Batista B, Moreno-Vega JM (2013) Hybrid estimation of distribution algorithm for the quay crane scheduling problem. Appl Soft Comput 13(10):4063–4076

    Article  Google Scholar 

  13. Expósito-Izquierdo C, Lalla-Ruiz E, de Armas J, Melián-Batista B, Moreno-Vega JM (2015) A heuristic algorithm based on an improvement strategy to exploit idle time periods for the stacking problem. Comput Ind Eng 87:410–424

    Article  Google Scholar 

  14. Expósito-Izquierdo C, Melián-Batista B, Moreno-Vega JM (2015) An exact approach for the blocks relocation problem. Expert Syst Appl 42(17–18):6408–6422

    Article  Google Scholar 

  15. Gharehgozli AH, Yu Y, de Koster R, Udding JT (2014) An exact method for scheduling a yard crane. Eur J Oper Res 235(2):431–447. Maritime Logistics.

    Google Scholar 

  16. Henesey L (2006) Overview of transshipment operations and simulation. In: MedTrade conference, pp 6–7

    Google Scholar 

  17. Imai A, Nishimura E, Papadimitriou S (2001) The dynamic berth allocation problem for a container port. Transp Res Part B Methodol 35(4):401–407

    Article  Google Scholar 

  18. Kim KH, Park YM (2004) A crane scheduling method for port container terminals. Eur J Oper Res 156(3):752–768

    Article  MATH  Google Scholar 

  19. Korsvik JE, Fagerholt K (2010) A tabu search heuristic for ship routing and scheduling with flexible cargo quantities. J Heuristics 16(2):117–137

    Article  MATH  Google Scholar 

  20. Lalla-Ruiz E, Melián-Batista B, Moreno-Vega JM (2012) Artificial intelligence hybrid heuristic based on tabu search for the dynamic berth allocation problem. Eng Appl Artif Intell 25(6):1132–1141

    Article  Google Scholar 

  21. Meisel F, Bierwirth C (2013) A framework for integrated berth allocation and crane operations planning in seaport container terminals. Transp Sci 47(2):131–147

    Article  Google Scholar 

  22. Monaco MF, Sammarra M, Sorrentino G (2014) The terminal-oriented ship stowage planning problem. Eur J Oper Res 239(1):256–265

    Article  MATH  Google Scholar 

  23. Rei RJ, Pedroso JP (2012) Heuristic search for the stacking problem. Int Trans Oper Res 19(3):379–395

    Article  MathSciNet  MATH  Google Scholar 

  24. Shang J (2010) A heuristic algorithm for the integrated yard truck scheduling in container terminal with twin 40-foot quay crane. In: 2010 international conference on computer, mechatronics, control and electronic engineering, Piscataway, vol 2, pp 386–389

    Google Scholar 

  25. United Nations Conference on Trade and Development. Review of maritime transport (2014)

    Google Scholar 

Download references

Acknowledgements

This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (projects TIN2012-32608 and TIN2015-70226-R) and with FEDER funds.

Author information

Authors and Affiliations

  1. Department of Computer Engineering and Systems, Universidad de La Laguna, Tenerife, San Cristóbal de La Laguna, Spain

    Christopher Expósito-Izquierdo, Eduardo Lalla-Ruiz, Jesica de Armas, Belén Melián-Batista & J. Marcos Moreno-Vega

Authors
  1. Christopher Expósito-Izquierdo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eduardo Lalla-Ruiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jesica de Armas
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Belén Melián-Batista
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. Marcos Moreno-Vega
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christopher Expósito-Izquierdo .

Editor information

Editors and Affiliations

  1. Department of Statistics and Operations, University of Valencia, Valencia, Spain

    Rafael Martí

  2. University of Florida Industrial and Systems Engineering, Gainesville, Florida, USA

    Pardalos Panos

  3. Modeling and Optimization Group, Amazon (United States) , Seattle, Washington, USA

    Mauricio G. C. Resende

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this entry

Cite this entry

Expósito-Izquierdo, C., Lalla-Ruiz, E., de Armas, J., Melián-Batista, B., Moreno-Vega, J.M. (2017). Maritime Container Terminal Problems. In: Martí, R., Panos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07153-4_57-1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-07153-4_57-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07153-4

  • Online ISBN: 978-3-319-07153-4

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation