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Cooperative relations among intermodal hubs and transport providers at freight networks using an MPC approach

  • João Lemos Nabaisc, d(Author)
    ,
  • Rudy R. Negenborne(Author)
    ,
  • ,
  • Miguel Ayala Bottoc(Author)
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer review

Publication Information

Tipo di output

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer review

Lingua originale

English

Pagine da-a (Numero di pagine)

Pagine 478-494 (17 pagine)

Attività cardine della pubblicazione

  • Published - 01/01/2015

Stato pubblicazione

Published - 01/01/2015

Editore/-rice

Springer Verlag

Serie di pubblicazioni

  • Nome della serie di pubblicazioni: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    ISSN (cartaceo): 0302-9743
    ISSN (elettronico): 1611-3349
    Volume: 9335
9783319242637

ID pubblicazione esterna

  • Scopus: 84951028932

Titolo pubblicazione host

Computational Logistics - 6th International Conference, ICCL 2015, Proceedings

Editor pubblicazione host

  • Stefan Voß
  • Rudy R. Negenborn
  • Francesco Corman
  • Rudy R. Negenborn
  • Rudy R. Negenborn

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.