Anticipatory freight scheduling in synchromodal transport

Arturo Eduardo Pérez Rivera

Research output: ThesisPhD Thesis - Research UT, graduation UT

243 Downloads (Pure)

Abstract

We study anticipatory scheduling decisions for the transport of freight in a synchromodal network. In a synchromodal network, the choice of mode, the choice of transport path, and the timing of operations is not fixed up front, but decided upon various moments using the latest information about the status of the transport modes and about freight demand. This increased flexibility brings opportunities for consolidation and options for efficient transport, throughout the network and throughout time. However, to achieve such gains, transport decisions must consider their consequences in the entire network and anticipate on their effect in future decisions. We use four different perspectives for studying the decisions in a synchromodal network, based on traditional scheduling methods for multi-modal transport considered in the literature. For each perspective, we develop mathematical models and heuristic algorithms that support anticipatory scheduling decisions in synchromodal transport. Furthermore, for each perspective, we evaluate the output of our models and algorithms using simulation-based experiments, and provide insights into their efficiency gains over traditional scheduling methods, using different network characteristics. As an addition to the development of scheduling methods, we study how to increase the awareness about the trade-offs considered by our methods and how to facilitate the adoption of our algorithms through a serious game. Finally, we present a closing reflection about our anticipatory scheduling methods for freights in synchromodal transport, and provide an outlook for further research with respect to extensions of the models, improvements of the heuristics, and implementation aspects.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • van Hillegersberg, Jos , Supervisor
  • Mes, Martijn R.K., Co-Supervisor
Award date29 Jun 2018
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-4571-6
DOIs
Publication statusPublished - 29 Jun 2018

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