Re-marshalling Problem

  • Filip Covic
Part of the Contributions to Management Science book series (MANAGEMENT SC.)


Addressing the practice-orientated research questions of the work, a heuristic solution method is developed and operational tools are assessed that are apt for practical yard block operations within an online environment. As a consequence, this chapter is focused on a simulation-based approach which enables the testing of real-world cases. In this context, the Re-marshalling Problem is analysed in detail which is expected to be highly relevant to optimising container handling in yard blocks. Moreover, re-marshalling is the primary container handling type to be performed for making use of improved external truck arrival information during the dwell time of containers in the yard block. In this context, the Re-marshalling Problem is targeted within the front-end block layout embedded in full yard block operations. The combination of this environment and the underlying assumptions demonstrate a novel viewpoint on the Re-marshalling Problem which altogether has been scarcely covered in comparison to the more prominent container handling problems in the literature. Thus, the study in this chapter can be characterised as empirical study addressing practice-orientated terminal implementation and providing insights for terminal planners and operators regarding efficient yard block operations.


  1. Angeloudis P, Bell MGH (2011) A review of container terminal simulation models. Marit Policy Manag 38(5):523–540CrossRefGoogle Scholar
  2. Banks J, Carson JS II, Nelson BL, Nicol DM (2010) Discrete-event system simulation, 5th edn. Pearson, New JerseyGoogle Scholar
  3. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57(1):289–300Google Scholar
  4. Bojadziev G, Bojadziev M (2007) Fuzzy logic, for business, finance, and management. Volume 23 of advances in fuzzy systems – applications and theory, 2nd edn. World Scientific, SingaporeGoogle Scholar
  5. Caserta M, Schwarze S, Voß S (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 247–269Google Scholar
  6. Caserta M, Schwarze S, Voß S (2012) A mathematical formulation and complexity considerations for the blocks relocation problem. Eur J Oper Res 219(1):96–104CrossRefGoogle Scholar
  7. Choe R, Kim TS, Kim T, Ryu KR (2015) Crane scheduling for opportunistic remarshaling of containers in an automated stacking yard. Flex Serv Manuf J 27(2–3):331–349CrossRefGoogle Scholar
  8. Covic F (2017) Re-marshalling in automated container yards with terminal appointment systems. Flex Serv Manuf J 29(3–4):433–503CrossRefGoogle Scholar
  9. Dragović B, Tzannatos E, Park NK (2017) Simulation modelling in ports and container terminals: literature overview and analysis by research field, application area and tool. Flex Serv Manuf J 29(1):4–34CrossRefGoogle Scholar
  10. Duinkerken MB, Evers JJM, Ottjes JA (2001) A simulation model for integrating quay transport and stacking policies on automated container terminals. In: Proceedings of the 15th European simulation multiconference, Prague, pp 909–916Google Scholar
  11. Galle V, Barnhart C, Jaillet P (2018) A new binary formulation of the restricted container relocation problem based on a binary encoding of configurations. Eur J Oper Res 267(2):467–477CrossRefGoogle Scholar
  12. Kang J, Oh MS, Ahn EY, Ryu KR, Kim KH (2006a) Planning for intra-block remarshalling in a container terminal. In: Ali M, Dapoigny R (eds) Advances in applied artificial intelligence, IEA/AIE 2006. Volume 4031 of lecture notes in computer science, pp 1211–1220. Springer, Berlin/HeidelbergGoogle Scholar
  13. Kang J, Ryu KR, Kim KH (2006b) Deriving stacking strategies for export containers with uncertain weight information. J Int Manag 17(4):399–410Google Scholar
  14. Kemme N (2011) RMGC simulation model – documentation of a simulation model for automated rail-mounted-gantry-crane systems at seaport container terminals., Institute for Operations Research, University of Hamburg. Accessed on 07 Mar 2018
  15. Kemme N (2013) Design and operation of automated container storage systems. Contributions to management science, 1st edn. Physica, HeidelbergGoogle Scholar
  16. Lee Y, Hsu NY (2007) An optimization model for the container pre-marshalling problem. Comput Oper Res 34(11):3295–3313CrossRefGoogle Scholar
  17. Lehnfeld J, Knust S (2014) Loading, unloading and premarshalling of stacks in storage areas: survey and classification. Eur J Oper Res 239(2):297–312CrossRefGoogle Scholar
  18. Park K, Park T, Ryu KR (2009) Planning for remarshaling in an automated container terminal using cooperative coevolutionary algorithms. In: Proceedings of the 2009 ACM symposium on applied computing, SAC 2009, Honolulu, pp 1098–1105Google Scholar
  19. Pedrycz W (1994) Why triangular membership functions? Fuzzy Sets Syst 64(1):21–30CrossRefGoogle Scholar
  20. Petering MEH (2009) Effect of block width and storage yard layout on marine container terminal performance. Transp Res E Log Transp Rev 45(4):591–610CrossRefGoogle Scholar
  21. Ries J, González-Ramírez RG, Miranda P (2014) A fuzzy logic model for the container stacking problem at container terminals. In: González-Ramírez RG, Schulte F, Voß S, Ceroni Díaz JA (eds) Computational logisitcs, ICCL 2014. Volume 8760 of lecture notes in computer science. Springer, Cham, pp 93–111Google Scholar
  22. Tanaka S, Mizuno F (2018) An exact algorithm for the unrestricted block relocation problem. Comput Oper Res 95:12–31CrossRefGoogle Scholar
  23. van Asperen E, Borgman B, Dekker R (2013) Evaluating impact of truck announcements on container stacking efficiency. Flex Serv Manuf J 25(4):543–556CrossRefGoogle Scholar
  24. Wilcoxon F (1945) Individual comparisons by ranking methods. Biom Bull 1(6):80–83CrossRefGoogle Scholar
  25. Yu VF, Cheng HY, Ting HI (2009) Optimizing re-marshalling operation in export container terminals. In: Proceedings of the Asia Pacific industrial engineering & management systems conference, APIEMS 2009, Kitakyushu, pp 2934–2938Google Scholar
  26. Zimmermann HJ (2001) Fuzzy set theory and its applications, 4th edn. Kluwer, DordrechtCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Filip Covic
    • 1
  1. 1.Institute for Operations Research, HBS Hamburg Business SchoolUniversity of HamburgHamburgGermany

Personalised recommendations