Vessel Rotation Planning - A Layered Distributed Constraint Optimization Approach

Shijie Li, Rudy R. Negenborn, Gabriel Lodewijks

Abstract

Vessel rotation planning concerns the problem of assigning rotations to vessels over a number of terminals for loading and unloading containers in a large port. Vessel operators and terminal operators communicate with each other to make appointments about the rotation plans for the vessels. However, it happens frequently that these appointments cannot be met. Thus, it is important to generate the rotation plans for the vessel operators in an efficient automated way. In this paper, we propose an approach to solve the vessel rotation planning problem by modeling the problem as a layered distributed constraint optimization problem (DCOP). To evaluate the performance of the proposed approach, combinations of three DCOP algorithms are considered, namely, Asynchrounous Forward Bounding, Synchrounous Branch and Bound, and Dynamic Programming Optimization Protocol. We evaluate the solution quality and computational and communication costs of these three algorithms when solving the vessel rotation planning problem using the proposed layered formulation.

References

  1. Douma, A. (2008). Aligning the operations of barges and terminals through distributed planning. PhD thesis, University of Twente, Enschede, The Netherlands.
  2. Douma, A., Schutten, M., and Schuur, P. (2009). Waiting profiles: An efficient protocol for enabling distributed planning of container barge rotations along terminals in the port of rotterdam. Transportation Research Part C: Emerging Technologies, 17(2):133-148.
  3. Douma, A., van Hillegersberg, J., and Schuur, P. (2012). Design and evaluation of a simulation game to introduce a multi-agent system for barge handling in a seaport. Decision Support Systems, 53(3):465-472.
  4. Gershman, A., Meisels, A., and Zivan, R. (2009). Asynchronous forward bounding for distributed cops. Journal of Artificial Intelligence Research, 34(1):61- 88.
  5. Hirayama, K. and Yokoo, M. (1997). Distributed partial constraint satisfaction problem. In Proceedings of the 3rd International Conference on Principles and Practice of Constraint Programming, pages 222-236. Springer, Linz, Austria.
  6. Hosseini, S., Samaneh, and Basir, O. A. (2013). Target to sensor allocation: A hierarchical dynamic distributed constraint optimization approach. Computer Communications, 36(9):1024-1038.
  7. Léauté, T., Ottens, B., and Szymanek, R. (2009). FRODO 2.0: An open-source framework for distributed constraint optimization. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, pages 160-164, Pasadena, California, USA.
  8. Li, S., Negenborn, R., and Lodewijks, G. (2014). A distributed constraint optimization approach for vessel rotation planning. In Proceedings of the 5th International Conference on Computational Logistics, pages 61-80, Valparaso, Chile.
  9. Melis, M., Miller, I., Kentrop, M., Van Eck, B., Leenaarts, M., Schut, M., and Treur, J. (2003). Distributed rotation planning for container barges in the port of rotterdam. Intelligent Logistics Concepts, pages 101- 116.
  10. Modi, P. J., Shen, W.-M., Tambe, M., and Yokoo, M. (2005). Adopt: Asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence, 161(1):149-180.
  11. Moonen, H., Van de Rakt, B., Miller, I., Van Nunen, J., and Van Hillegersberg, J. (2007). Agent technology supports inter-organizational planning in the port. Managing Supply Chains: Challenges and Opportunities, pages 201-225.
  12. Petcu, A. (2009). A class of algorithms for distributed constraint optimization. PhD thesis, Ócole Polytechnique Fédérale de Lausanne, Lausanne, Switherland.
  13. Petcu, A. and Faltings, B. (2005a). Approximations in distributed optimization. In Principles and Practice of Constraint Programming, pages 802-806. Springer.
  14. Petcu, A. and Faltings, B. (2005b). A scalable method for multiagent constraint optimization. In Proceedings of the 19th International Joint Conference on Artificial Intelligence, volume 5, pages 266-271, Edingurgh, Scotland.
  15. Rossi, F., Van Beek, P., and Walsh, T. (2006). Handbook of Constraint Programming. Elsevier.
  16. Schut, M. C., Kentrop, M., Leenaarts, M., Melis, M., and Miller, I. (2004). Approach: Decentralised rotation planning for container barges. In Proceedings of the 16th European Conference on Artificial Intelligence, pages 755-759, Valencia, Spain.
Download


Paper Citation


in Harvard Style

Li S., R. Negenborn R. and Lodewijks G. (2015). Vessel Rotation Planning - A Layered Distributed Constraint Optimization Approach . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-073-4, pages 166-173. DOI: 10.5220/0005202801660173


in Bibtex Style

@conference{icaart15,
author={Shijie Li and Rudy R. Negenborn and Gabriel Lodewijks},
title={Vessel Rotation Planning - A Layered Distributed Constraint Optimization Approach},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2015},
pages={166-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005202801660173},
isbn={978-989-758-073-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Vessel Rotation Planning - A Layered Distributed Constraint Optimization Approach
SN - 978-989-758-073-4
AU - Li S.
AU - R. Negenborn R.
AU - Lodewijks G.
PY - 2015
SP - 166
EP - 173
DO - 10.5220/0005202801660173