Abstract
The berth scheduling problem deals with the assignment of vessels to berths in a marine terminal, with the objective to maximize the ocean carriers’ satisfaction (minimize delays) and/or minimize the terminal operator's costs. In the existing literature, two main assumptions are made regarding the status of a vessel: (a) either all vessels to be served are already in the port before the planning period starts, or (b) they are scheduled to arrive after the planning period starts. The latter case assumes an expected time of arrival for each vessel, which is a function of the departure time of the vessel from the previous port, the average operating speed and the distance between the two ports. Recent increases in fuel prices have forced ocean carriers to reduce current operating speeds, while stressing to terminal operators the need to maintain the integrity of their schedule. In addition, several collaborative efforts between industry and government agencies have been proposed, aiming to reduce emissions from marine vessels and port operations. In light of these issues, this article presents a berth-scheduling policy to minimize vessel delayed departures and indirectly reduce fuel consumption and emissions produced by the vessels while in idle mode. Vessel arrival times are considered as a variable and are optimized to accommodate the objectives of the proposed policy while providing ocean carriers with an optimized vessel speed. Example problems using real data show that the proposed policy reduces the amount of emissions produced by vessels at the port in idle mode, optimizes fuel consumption and waiting time at the port by reducing vessel operating speeds to optimal levels and minimizes the effects of late arrivals to the ocean carriers’ schedule.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The term hotelling refers to vessels using their auxiliary engines while docked in order to provide electrical power to the ship for climate control, lighting, cargo refrigeration, on-board cargo handling equipment, and other uses.
References
Fossey, J. (2008) In the bunker. CI-Online, http://www.ci-online.co.uk/, accessed 19 September 2008.
Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization, and Machine-Learning. Reading, MA: Addison-Wesley.
Golias, M. (2007) The discrete and dynamic berth allocation problem: Models and algorithms. PhD Dissertation, Rutgers University, NJ.
Guan, Y. and Cheung, R.K. (2004) The berth allocation problem: Models and solution methods. OR Spectrum 26: 75–92.
Hansen, P., Oguz, C. and Mladenovic, N. (2008) Variable neighborhood search for minimum cost berth allocation. European Journal of Operational Research 131: 636–649.
Hooker, N.J. (1998) Constraint satisfaction methods for generating valid cuts, http://Citeseer.Ist.Psu.Edu/163317.html, accessed 19 September 2008.
Imai, A., Chen, H.C., Nishimura, E. and Papadimitriou, S. (2008) The simultaneous berth and quay crane allocation problem. Transportation Research Part E 44 (5): 900–920.
Imai, A., Nagaiwa, K. and Tat, C.-W. (1997) Efficient planning of berth allocation for container terminals in Asia. Journal of Advanced Transportation 31: 75–94.
Imai, A., Nishimura, E. and Papadimitriou, S. (2001) The dynamic berth allocation problem for a container port. Transportation Research Part B 35: 401–417.
Imai, A., Nishimura, E. and Papadimitriou, S. (2003) Berth allocation with service priority. Transportation Research Part B 37: 437–457.
Imai, A., Sun, X., Nishimura, E. and Papadimitriou, S. (2005) Berth allocation in a container port: Using continuous location space approach. Transportation Research Part B 39: 199–221.
Imai, A., Zhang, J.-T., Nishimura, E. and Papadimitriou, S. (2007) The berth allocation problem with service time and delay time objectives. Maritime Economics & Logistics 9 (4): 269–290.
Kim, K.H. and Moon, K.C. (2003) Berth scheduling by simulated annealing. Transportation Research Part B 37: 541–560.
Lazic, B.M. (2004) Container terminal operation emissions. West Coast Region Conference on Marine Port Air Quality Impacts. Seattle Tacoma.
Moorthy, R. and Teo, C.-P. (2006) Berth management in container terminal: The template design problem. OR Spectrum 28: 495–518.
Park, M.Y. and Kim, H.K.A. (2003) A scheduling method for berth and quay cranes. OR Spectrum 25: 1–23.
Pinedo, M. (2008) Scheduling: Theory, Algorithms, and Systems. Englewood Cliffs, NJ: Prentice Hall.
Steenken, D., Voss, S. and Stahlbock, R. (2004) Container terminal operation and operations research – A classification and literature review. OR Spectrum 26: 3–49.
Taboada, H. (2007) Multi-objective optimization algorithms considering objective preferences and solution clusters. PhD Dissertation, Rutgers University, NJ.
Theofanis, S., Boile, M. and Golias, M.M. (2009) Container Terminal Berth Planning: Critical Review of Research Approaches and Practical Challenges. Marine Transportation and Port Operations 2009: Transportation Research Board 2100, pp. 22–28.
Wacket, M. (2007) A rollercoaster year in 2007: A white-knuckle ride in 2008? CI-Online, http://www.ci-online.co.uk/, accessed 19 September 2008.
Acknowledgements
This article is based on work supported by the National Science Foundation under grants No. 0538901 and No. 0625515, and by the Environmental Bioinformatics and Computational Toxicology Center under grant GAD R832721-010. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors would like to thank the anonymous referees for their constructive comments.
Author information
Authors and Affiliations
Corresponding author
Appendices
Appendix A
Subject to:
where
Appendix B
Subject to:
Rights and permissions
About this article
Cite this article
Golias, M., Saharidis, G., Boile, M. et al. The berth allocation problem: Optimizing vessel arrival time. Marit Econ Logist 11, 358–377 (2009). https://doi.org/10.1057/mel.2009.12
Published:
Issue Date:
DOI: https://doi.org/10.1057/mel.2009.12