Abstract
Inland waterways management is likely to go through heavy changes due to an expected traffic increase in a context of climate change. Those changes are going to require adaptive and resilient management of the water resource. A representative model of the inland waterway has been proposed, using Markov decision processes to model the dynamic and uncertainties of the waterway. It is used to obtain an optimal plan for the distribution of the water on the network that takes into account the uncertainties arising for the operation of such networks. A subnetwork of the Hauts-de-France is modeled using this approach based on real data of traffic and water levels. The produced plans are tested on different scenarios under expected and unexpected conditions of traffic and climate to observe the quality and resilience of the generated plan during its execution. Simulations will show the advantages and limitations of such a modeling of the inland waterway network.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
IPCC. (2014). Climate change 2014. The Core Writing Team, R. K. Pachauri & L. Meyer, Synthesis Report.
Mallidis, I., Dekker, R., & Vlachos, D. (2012). The impact of greening on supply chain design and cost: A case for a developing region. Special Section on Rail Transit Systems and High Speed Rail, 22, 118–128.
Mihic, S., Golusin, M., & Mihajlovic, M. (2011). Policy and promotion of sustainable inland waterway transport in Europe—Danube River. Renewable and Sustainable Energy Reviews, 15(4), 1801–1809.
Pachauri, R. K., Allen, M., Barros, V., Broome, J., Cramer, W., Christ, R., et al. (2014). Contribution of Working in Groups I, II and III to the Fifth Assesment Report of the Intergovernmental Panl on Climate Change, Climate Change 2014: Synthesis Report.
Beuthe, M., Jourquin, B., Urbain, N., Lingemann, I., & Ubbles, B. (2014). Climate change impacts on transport on the Rhine and Danube: A multimodal approach. Transportation Reasearch Part D: Transport and Environment, 27, 6–11.
Nouasse, H., Horvàth, K., Rajaoarisoa, L., Doniec, A., Duviella, E., & Chuquet, K. (2016). Study of global change impacts on the inland navigation management: Application on the Nord-Pas de Calais network. Transportation Research Procedia, 14, 4–13.
Desquesnes, G., Lozenguez, G., Doniec, A., & Duviella, E. (2016). Planning large systems with MDPs: Case study of inland waterways supervision. Advances in Distributed Computing and Artificial Intelligence Journal, 5(4), 71–84.
Brand, C., Tran, M., & Anable, J. (2012). The UK transport carbon model: An integrated life cycle approach to explore low carbon futures. Energy Policy, 41, 107–124.
Bellman, R. (1957). A Markovian decision process. Journal of Mathematics and Mechanics, 6(4), 679–684.
Putterman, M. L. (1994). Markov decision processes: Discrete stochastic dynamic programming. Wiley.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Desquesnes, G., Lozenguez, G., Doniec, A., Duviella, É. (2018). Large Markov Decision Processes Based Management Strategy of Inland Waterways in Uncertain Context. In: Gourbesville, P., Cunge, J., Caignaert, G. (eds) Advances in Hydroinformatics . Springer Water. Springer, Singapore. https://doi.org/10.1007/978-981-10-7218-5_1
Download citation
DOI: https://doi.org/10.1007/978-981-10-7218-5_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7217-8
Online ISBN: 978-981-10-7218-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)