A Global Intermodal Shipment Matching Problem Under Travel Time Uncertainty

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Global intermodal transportation involves the movement of shipments between inland terminals located in different continents by using ships, barges, trains, trucks, or any combination among them through integrated planning at a network level. One of the challenges faced by global operators is the matching of shipment requests with transport services in an integrated global network. The characteristics of the global intermodal shipment matching problem include acceptance and matching decisions, soft time windows, capacitated services, and transshipments between multimodal services. The objective of the problem is to maximize the total profits which consist of revenues, travel costs, transfer costs, storage costs, delay costs, and carbon tax. Travel time uncertainty has significant effects on the feasibility and profitability of matching plans. However, travel time uncertainty has not been considered in global intermodal transport yet leading to significant delays and infeasible transshipments. To fill in this gap, this paper proposes a chance-constrained programming model in which travel times are assumed stochastic. We conduct numerical experiments to validate the performance of the stochastic model in comparison to a deterministic model and a robust model. The experiment results show that the stochastic model outperforms the benchmarks in total profits.

Original languageEnglish
Title of host publicationComputational Logistics
Subtitle of host publicationProceedings of the 11th International Conference, ICCL 2020
EditorsEduardo Lalla-Ruiz, Martijn Mes, Stefan Voß
Place of PublicationCham, Switzerland
ISBN (Electronic)978-3-030-59747-4
ISBN (Print)978-3-030-59746-7
Publication statusPublished - 2020
Event11th International Conference on Computational Logistics, ICCL 2020 - Enschede, Netherlands
Duration: 28 Sep 202030 Sep 2020

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Computational Logistics, ICCL 2020


  • Chance-constrained programming
  • Global intermodal transportation
  • Shipment matching problem
  • Travel time uncertainty

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