Discrete Time Model and Algorithms for Container Yard Crane Scheduling

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Abstract

Container terminal (CT) operations are often bottlenecked by slow yard crane (YC) movements. Prime mover (PM) queues in front of the YCs are common. Hence efficient YC scheduling to reduce the PM waiting time is critical in increasing a CT’s throughput. In this chapter, we develop an efficient model for YC scheduling by taking into account realistic operational constraints such as inter-crane interference, fixed YC separation distances, and simultaneous container storage/retrievals. Among them, only inter-crane interference has ever been considered in the literature. The model requires far fewer integer variables than the literature by using bi-index decision variables. We show how the model can be solved quickly using heuristics and rolling-horizon algorithm, yielding close to optimal solutions in seconds. The solution quality and solution time are both better than the literature even with additional constraints considered. The proposed formulations and algorithms can be extended to other problems with time windows and space constraints.

Keywords

Scheduling Rolling-horizon algorithm Container yard MILP 
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References

  1. Bish E. K. A (2003) multiple-crane-constrained scheduling problem in a container terminal. European Journal of Operational Research. 144; 83–107.Google Scholar
  2. Chen L., Bostel N., Dejax P., Cai J., Xi L. (2007) A tabu search algorithm for the integrated scheduling problem of container handling systems in a maritime terminal. European Journal of Operational Research. 181: 40–58.Google Scholar
  3. Cheung R. K., Li C., and Lin W. (2002) Interblock crane deployment in container terminals. Transportation Science. 36:79–93.Google Scholar
  4. Froyland G.., Koch T., Megow N., Duane E., Wren H. (2008) Optimizing the landside operation of a container terminal. OR Spectrum. 30:53–75.Google Scholar
  5. Henwood Rachel (2006) The practitioner’s definitive guide: seafreight forwarding, SNP Reference.Google Scholar
  6. Hopp W. J., Spearman M. L. (2000) Factory Physics: foundations of manufacturing management, Irwin/McGraw-Hill.Google Scholar
  7. Kim K. H. and Kim K. Y. (1999) An optimal routing algorithm for a transfer crane in port container terminals. Transportation Science. 33:17–33.Google Scholar
  8. Kim K. Y. and Kim K. H. (2003) Heuristic algorithms for routing yard-side equipment for minimizing loading times in container terminals. Naval Research Logistics. 50:498–514.Google Scholar
  9. Kim K. H., Park Y. (2004) A crane scheduling method for port container terminals. European Journal of Operational Research. 156:752–768.Google Scholar
  10. Lim A., Rodrigues B., Xu Z. (2007) A m-Parallel Crane Scheduling Problem with a Non-crossing Constraint. Naval Research Logistics. 54:115–127.Google Scholar
  11. Li J., Leung S., Wu Y., Liu K. (2007) Allocation of empty containers between multi-ports. European Journal of Operational Research. 182:400–412.Google Scholar
  12. Narasimhan A. and Palekar U. S. (2002) Analysis and algorithms for the transtainer routing problem in container port operations. Transportation Science. 36:63–78.Google Scholar
  13. Ng, W. C.(2005) Crane scheduling in container yards with inter-crane interference. European Journal of Operational Research. 164:64–78.Google Scholar
  14. Ng W. C. and Mak, K. L. (2005) Yard crane scheduling in port container terminals. Applied Mathematical Modelling. 29:263–275.Google Scholar
  15. Ng W. C. and Tsang, W. S. (2005) Scheduling yard crane in a port container terminal using genetic algorithm. The First International Conference on Transportation Logistics (T-Log 2005), 27–29 July 2005; Singapore.Google Scholar
  16. Stahlbock R., Voß S. (2008) Operations research at container terminals: a literature update. OR Spectrum. 30:1–52.Google Scholar
  17. Steenken D., Voß S., Stahlbock R. (2004) Container terminal operation and operations research—a classification and literature review. OR Spectrum. 26:3–49.Google Scholar
  18. Vis I. F. A., Koster R.D. (2003) Transshipment of containers at a container terminal: an overview. European Journal of Operational Research.147:1–16.Google Scholar
  19. Wang F., Lim A. (2007) A stochastic beam search for the berth allocation problem. Decision Support Systems. 42:2186–2196.Google Scholar
  20. Zhang C., Wan Y., Liu J., and Linn R. J. (2002) Dynamic crane deployment in container storage yards. Transportation Research B. 36:537–555.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Graduate School of International ManagementInternational University of JapanNiigataJapan
  2. 2.Department of International Business and Asian Studies, Gold Coast CampusGriffith UniversitySouthportAustralia
  3. 3.School of Business IT and Logistics, Platform Technologies Research InstituteRMIT UniversityMelbourneAustralia

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