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Container Rehandling at Maritime Container Terminals

  • Marco CasertaEmail author
  • Silvia Schwarze
  • Stefan Voß
Chapter
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 49)

Abstract

In this paper, we review recent contributions dealing with the rehandling of containers at maritime container terminals. The problems studied in the paper refer to a post-stacking situation, i.e. problems arising after the stacking area has already been arranged. In order to increase efficiency of loading/unloading operations, once updated information about the state of the containers as well as of the vessels becomes available, it is possible to reshuffle the container yard, or a portion of it, in such a way that future loading operations are carried out with maximal efficiency. The increase in efficiency of loading/unloading operations has a bearing on the berthing time of the vessels, which, in turn, is a widely accepted indicator of port efficiency. Three types of post-stacking problems have been identified, namely (i) the remarshalling problem, (ii) the premarshalling problem, and (iii) the relocation problem. With respect to each of these problems, a thorough explanation of the problem itself, its relevance and its connections with other container handling issues are offered. In addition, algorithmic approaches to tackle such problems are summarized.

Keywords

Container Terminal Container Handling Export Container Target Container Stowage Plan 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Bazzazi M, Safaei N, Javadian N (2009) A genetic algorithm to solve the storage space allocation problem in a container terminal. Computers and Industrial Engineering 56(1):44–52CrossRefGoogle Scholar
  2. Caserta M, Voß S (2009) A Corridor Method-based Algorithm for the Premarshalling Problem. In: Giacobini M, Brabazon A, Cagnoni S, Di Caro G, Ekart A, Espacia-Alcázar A, Farooq M, Fink A, Machado P, McCormack J, O’Neill M, Neri F, Preuss M, Rothlauf F, Tarantino E, Yang S (eds) Applications of Evolutionary Computing, Lecture Notes in Computer Science, vol 5484, Springer, Berlin, pp 788–797Google Scholar
  3. Caserta M, Schwarze S, Voß S (2009a) A New Binary Description of the Blocks Relocation Problem and Benefits in a Look Ahead Heuristic. In: Cotta C, Cowling P (eds) Evolutionary Computation in Combinatorial Optimization, Lecture Notes in Computer Science, vol 5482, Springer, Berlin, pp 37–48CrossRefGoogle Scholar
  4. Caserta M, Schwarze S, Voß S (2009b) A mathematical formulation and complexity considerations for the blocks relocation problem, Working Paper, Institute of Information Systems, University of HamburgGoogle Scholar
  5. Caserta M, Voß S, Sniedovich M (2009c) Applying the corridor method to a blocks relocation problem. OR Spectrum (DOI: 10.1007/s00291-009-0176-5)Google Scholar
  6. Choe R, Park T, Oh MS, Kang J, Ryu KR (2009) Generating a rehandlingfree intra-block remarshaling plan. Journal of Intelligent Manufacturing (DOI: 10.1007/s10845-009-0273-y)Google Scholar
  7. Dekker R, Voogd P, van Asperen E (2006) Advanced methods for container stacking. OR Spectrum 28(4):563–586CrossRefGoogle Scholar
  8. Felsner S, Pergel M (2008) The Complexity of Sorting with Networks of Stacks and Queues. In: Halperin D, Mehlhorn K (eds) Algorithms – ESA 2008: 16th Annual European Symposium, Lecture Notes in Computer Science, vol 5193, Springer, Berlin, pp 417–429Google Scholar
  9. Froyland G, Koch T, Megow N, Duane E, Wren H (2008) Optimizing the landside operation of a container terminal. OR Spectrum 30(1):53–75CrossRefGoogle Scholar
  10. Gambardella LM, Rizzoli AE, Zaffalon M (1998) Simulation and planning of an intermodal container terminal. Simulation 71(2):107–116CrossRefGoogle Scholar
  11. Gupta N, Nau DS (1992) On the complexity of blocks-world planning. Artificial Intelligence 56(2–3):223–254CrossRefGoogle Scholar
  12. Han Y, Lee LH, Chew EP, Tan KC (2008) A yard storage strategy for minimizing traffic congestion in a marine container transshipment hub. OR Spectrum 30(4):697–720CrossRefGoogle Scholar
  13. 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, Lecture Notes in Artificial Intelligence, Springer, Berlin, pp 1211–1220Google Scholar
  14. Kang J, Ryu KR, Kim KH (2006b) Deriving stacking strategies for export containers with uncertain weight information. Journal of Intelligent Manufacturing 17(4):399–410CrossRefGoogle Scholar
  15. Kim KH, Bae JW (1998) Re-marshalling export containers in port container terminals. Computers and Industrial Engineering 35(3–4):655–658CrossRefGoogle Scholar
  16. Kim KH, Hong GP (2006) A heuristic rule for relocating blocks. Computers & Operations Research 33(4):940–954CrossRefGoogle Scholar
  17. Kim KH, Park KT (2003) A note on a dynamic space-allocation method for outbound containers. European Journal of Operational Research 148(1):92–101CrossRefGoogle Scholar
  18. Kim KH, Park YM, Ryu KR (2000) Deriving decision rules to locate export containers in container yards. European Journal of Operational Research 124(1):89–101CrossRefGoogle Scholar
  19. Kozan E (2000) Optimising container transfers at multimodal terminals. Mathematical and Computer Modelling 31(10–12):235–243CrossRefGoogle Scholar
  20. Kozan E, Preston P (1999) Genetic algorithms to schedule container transfers at multimodal terminals. International Transactions in Operational Research 6(3):311–329CrossRefGoogle Scholar
  21. Kozan E, Preston P (2006) Mathematical modeling of container transfers and storage locations at seaport terminals. OR Spectrum 28(4):519–537CrossRefGoogle Scholar
  22. Lee LH, Chew EP, Tan KC, Han Y (2006) An optimization model for storage yard management in transshipment hubs. OR Spectrum 28(4):539–561CrossRefGoogle Scholar
  23. Lee Y, Chao SL (2009) A neighborhood search heuristic for pre-marshalling export containers. European Journal of Operational Research 196(2):468–475CrossRefGoogle Scholar
  24. Lee Y, Hsu NY (2007) An optimization model for the container pre-marshalling problem. Computers & Operations Research 34(11):3295–3313CrossRefGoogle Scholar
  25. Maniezzo V, Voß S, Stützle T (eds) (2009) Matheuristics: Hybridizing Metaheuristics and Mathematical Programming. Springer, BerlinGoogle Scholar
  26. Nishi T, Konishi M (2009) An optimisation model and its effective beam search heuristics for floor-storage warehousing systems. International Journal of Production Research (DOI: 10.1080/00207540802603767)Google Scholar
  27. Park C, Seo J (2009) Assembly block storage location assignment problem: revisited. Production Planning and Control 20(3):216–226CrossRefGoogle Scholar
  28. Park K, Park T, Ryu KR (2009) Planning for Remarshalling in an Automated Container Terminal using Cooperative Coevolutionary Algorithms. In: SAC ’09: Proceedings of the 2009 ACM Symposium on Applied Computing, ACM, New York, pp 1098–1105Google Scholar
  29. Preston P, Kozan E (2001) An approach to determine storage locations of containers at seaport terminals. Computers & Operations Research 28(10):983–995CrossRefGoogle Scholar
  30. Romero AG, Alquézar R (2004) To Block or Not to Block? In: Lemaitre C, Reyes C, Gonzalez J (eds) Advances in Artificial Intelligence – IBERAMIA 2004, Lecture Notes in Computer Science, vol 3315, Springer, Berlin, pp 134–143CrossRefGoogle Scholar
  31. Saccone S, Siri S (2009) An integrated simulation-optimization framework for the operational planning of seaport container terminals. Mathematical and Computer Modelling of Dynamical Systems 15(3):275–293CrossRefGoogle Scholar
  32. Stahlbock R, Voß S (2008) Operations research at container terminals: a literature update. OR Spectrum 30(1):1–52CrossRefGoogle Scholar
  33. Steenken D, Voß S, Stahlbock R (2004) Container terminal operations and operations research – a classification and literature review. OR Spectrum 26(1):3–49CrossRefGoogle Scholar
  34. Swisher JR, Hyden PD, Jacobson SH, Schruben LW (2000) Simulation Optimization: A Survey of Simulation Optimization Techniques and Procedures. In: WSC’00: Proceedings of the 32nd Conference onWinter Simulation, Society for Computer Simulation International, San Diego (California), pp 119–128Google Scholar
  35. Taleb-Ibrahimi M, De Castilho B, Daganzo CF (1993) Storage space vs handling work in container terminals. Transportation Research B 27B(1):13–32CrossRefGoogle Scholar
  36. Voß S (2008) Extended Mis-Overlay Calculation for Pre-Marshalling Containers. Technical Report, Institute of Information Systems, University of Hamburg, HamburgGoogle Scholar
  37. Yang JH, Kim KH (2006) A grouped storage method for minimizing relocations in block stacking systems. Journal of Intelligent Manufacturing 17(4):453–463CrossRefGoogle Scholar
  38. Yun WY, Choi YS (1999) Simulation model for container-terminal operation analysis using an object-oriented approach. International Journal of Production Economics 59(1):221–230CrossRefGoogle Scholar
  39. Zäpfel G, Wasner M (2006) Warehouse sequencing in the steel supply chain as a generalized job shop model. International Journal of Production Economics 104(2):482–501CrossRefGoogle Scholar
  40. Zhang C, Liu J, Wan Y, Murty KG, Linn RJ (2003) Storage space allocation in container terminals. Transportation Research B 37(10):883–903CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Institute of Information Systems – University of HamburgHamburgGermany

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