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Title: Should I Stay or Should I Go? Assessing Intermodal and Synchromodal Resilience from a Decentralized Perspective
Authors: AMBRA, Tomas 
Macharis, Cathy
Issue Date: 2019
Source: Sustainability, 11(6) (Art N° 1765)
Abstract: Synchromodal transport incorporates real-time events in a dynamic manner in order to facilitate the most suitable selection of modes, routes and handling points. Up until now, current assessments rely on analytical models. Most of these models average distances for barges and trains via route mapping platforms that provide realistic distances for road only. To reflect on real-world developments more accurately, new thinking and modelling approaches are necessary to bridge academic models with physical transport processes. This paper introduces a computational model which computes movements of agents in geographically referenced space. The model captures stochastic parallel processes for each mode, and simulates decentralized delivery performance of each order in terms of cost, time and emissions at an operational level. Furthermore, we study the routing of individual orders and their responsiveness to disruptions. Computational experiments are performed within a case study which concerns imports of retail goods by unimodal truck transport from France to Belgium. Our findings show that dynamic synchromodal solutions cope with disturbances better, but unnecessary deviations and pro-activeness can also lead to negative effects when compared to static intermodal solutions
Notes: Ambra, T (reprint author), Vrije Univ Brussel, MOBI Res Ctr, Pl Laan 2, B-1050 Brussels, Belgium. Hasselt Univ, Logist Res Grp, B-3590 Diepenbeek, Belgium. Res Fdn Flanders FWO, Egmontstr 5, B-1050 Brussels, Belgium.;;
Keywords: synchromodal transport; intermodal transport; Geographic information system (GIS); Agent-based modeling; simulation; disruption; resilience
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e-ISSN: 2071-1050
DOI: 10.3390/su11061765
ISI #: 000464354700008
Rights: Copyright 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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