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Hierarchical MPC for Multiple Commodity Transportation Networks

  • J. L. NabaisEmail author
  • R. R. Negenborn
  • R. B. Carmona-Benítez
  • L. F. Mendonça
  • M. A. Botto
Chapter
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 69)

Abstract

Transportation networks are large scale complex systems spatially distributed whose objective is to deliver commodities at the agreed time and at the agreed location. These networks appear in different domain fields, such as communication, water distribution, traffic, logistics and transportation. A transportation network has at the macroscopic level storage capability (located in the nodes) and transport delay (along each connection) as main features. Operations management at transportation networks can be seen as a flow assignment problem. The problem dimension to solve grows exponentially with the number of existing commodities, nodes and connections. In this work we present a Hierarchical Model Predictive Control (H-MPC) architecture to determine flow assignments in transportation networks, while minimizing exogenous inputs effects. This approach has the capacity to keep track of commodity types while solving the flow assignment problem. A flow decomposition of the main system into subsystems is proposed to diminish the problem dimension to solve in each time step. Each subsystem is managed by a control agent. Control agents solve their problems in a hierarchical way, using a so-called push-pull flow perspective. Further problem dimension reduction is achieved using contracted projection sets. The framework proposed can be easily scaled to network topologies in which hundreds of commodities and connections are present.

Keywords

Control Agent Center Node Transportation Network Container Terminal Quay Crane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was supported by the Portuguese Government, through Fundação para a Ciência e a Tecnologia, under the project PTDC/EEACRO/102102/2008 - AQUANET, through IDMEC under LAETA and by the VENI project “Intelligent multi-agent control for flexible coordination of transport hubs” (project 11210) of the Dutch Technology Foundation STW, a subdivision of the Netherlands Organisation for Scientific Research (NWO).

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • J. L. Nabais
    • 1
    Email author
  • R. R. Negenborn
    • 2
  • R. B. Carmona-Benítez
    • 3
  • L. F. Mendonça
    • 4
  • M. A. Botto
    • 5
  1. 1.IDMEC, Department of Informatics and Systems EngineeringSetúbal School of Technology, Polytechnical Institute of SetúbalSetúbalPortugal
  2. 2.Transport Engineering and LogisticsDelft University of TechnologyDelftThe Netherlands
  3. 3.School of Business and EconomicsUniversidad Anáhuac México NorteHuixquilucanMéxico
  4. 4.Department of Marine EngineeringEscola Superior Naútica Infante D. HenriquePaço d’ArcosPortugal
  5. 5.IDMEC, Instituto Superior TécnicoTechnical University of LisbonLisboaPortugal

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