Abstract
Freight networks are more exposed to unforeseen events leading to delays compromising the delivery of cargo on time. Cooperation among different parties present at freight networks are required to accommodate the occurrence of delays. Cargo assignment to the available transport capacity at the terminal is addressed using a Model Predictive Control approach in this paper, taking into consideration the final destination and the remaining time until due time of cargo. A cooperative framework for transport providers and intermodal hubs is proposed in this paper. The cooperation is based on information exchange regarding the amount of cargo at risk of not reaching the destination on time. The terminal searches for a faster connection at the terminal to allocate the cargo at risk such that the final destination is reached on time. The proposed heuristic is a step towards sustainable and synchromodal transportation networks. Simulation experiments illustrate the validity of these statements.
J.L. Nabais—This work was supported by FCT, through IDMEC, under LAETA, project UID/EMS/50022/2013.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Stahlbock, R., Voß, S.: Operations research at container terminals: a literature update. Operations Research Spectrum 30, 1–52 (2008)
Carlo, H.J., Vis, I.F.A., Roodbergen, K.J.: Transport operations in container terminals: Literature overview, trends, research directions and classification scheme. European Journal of Operational Research 236, 1–13 (2014)
Contargo, Contargo voert congestietoslag, tech. rep., Nieuwsblad Transport, July 16, 2007
Rodrigue, J.-P., Comtois, C., Slack, B.: The Geography of Transport Systems. Taylor and Francis Group (2006)
Ahuja, R., Magnanti, T., Orlin, J.: Network Flows. Prentice Hall (1993)
SteadieSeifi, M., Dellaert, N., Nuijten, W., van Woensel, T., Raoufi, R.: Multimodal freight transportation planning: A literature review. European Journal of Operations Research 233, 1–15 (2014)
Nabais, J.L., Negenborn, R.R., Botto, M.A.: Model predictive control for a sustainable transport modal split at intermodal container hubs. In: Proceeding of the 10th IEEE International Conference on Networking, Sensing and Control, Paris, pp. 591–596, April 2013
Maciejowski, J.: Predictive control with constraints. Prentice Hall, Harlow (2002)
Maestre, J., de la Pena, D.M., Camacho, E.: Distributed MPC: a supply chain case. In: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Shanghai, China, pp. 7099–7104, December 2009
Geyer, T., Larsson, M., Morari, M.: Hybrid emergency voltage control in power systems. In: Proceedings of the European Control Conference, Cambridge, UK (2003)
Negenborn, R.R., Overloop, P., Keviczky, T., De Schutter, B.: Distributed model predictive control of irrigation canals. Networks and Heterogeneous Media 4, 359–380 (2009)
Li, L., Negenborn, R.R., de Schutter, B.: A receding horizon approach for container flow assignment. Journal of the Transportation Research Board 2410, 132–140 (2014)
Alessandri, A., Sacone, S., Siri, S.: Modelling and optimal receding-horizon control of maritime container terminals. Journal of Mathematical Modeling and Algorithms 133, 6–109 (2007)
Nabais, J.L., Negenborn, R.R., Botto, M.A.: A novel predictive control based framework for optimizing intermodal container terminal operations. In: Hu, H., Shi, X., Stahlbock, R., Voß, S. (eds.) ICCL 2012. LNCS, vol. 7555, pp. 53–71. Springer, Heidelberg (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Nabais, J.L., Negenborn, R.R., Carmona-Benítez, R., Botto, M.A. (2015). Cooperative Relations Among Intermodal Hubs and Transport Providers at Freight Networks Using an MPC Approach. In: Corman, F., Voß, S., Negenborn, R. (eds) Computational Logistics. ICCL 2015. Lecture Notes in Computer Science(), vol 9335. Springer, Cham. https://doi.org/10.1007/978-3-319-24264-4_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-24264-4_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24263-7
Online ISBN: 978-3-319-24264-4
eBook Packages: Computer ScienceComputer Science (R0)