Dynamic Multi-period Freight Consolidation

Arturo Pérez Rivera, Martijn Mes

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
10 Downloads (Pure)


Logistic Service Providers (LSPs) offering hinterland transportation face the trade-off between efficiently using the capacity of long-haul vehicles and minimizing the first and last-mile costs. To achieve the optimal trade-off, freights have to be consolidated considering the variation in the arrival of freight and their characteristics, the applicable transportation restrictions, and the interdependence of decisions over time. We propose the use of a Markov model and an Approximate Dynamic Programming (ADP) algorithm to consolidate the right freights in such transportation settings. Our model incorporates probabilistic knowledge of the arrival of freights and their characteristics, as well as generic definitions of transportation restrictions and costs. Using small test instances, we show that our ADP solution provides accurate approximations to the optimal solution of the Markov model. Using larger problem instances, we show that our modeling approach has significant benefits when compared to common-practice heuristic approaches.
Original languageEnglish
Title of host publicationComputational Logistics
Subtitle of host publication6th International Conference, ICCL 2015, Delft, The Netherlands, September 23-25, 2015, Proceedings
EditorsFrancesco Corman, Stefan Voβ, Rudy R. Negenborn
Place of PublicationCham
ISBN (Electronic)978-3-319-24264-4
ISBN (Print)978-3-319-24263-7
Publication statusPublished - 2015
Event6th International Conference on Computational Logistics, ICCL 2015 - Delft, Netherlands
Duration: 24 Aug 201524 Aug 2015
Conference number: 6

Publication series

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


Conference6th International Conference on Computational Logistics, ICCL 2015
Abbreviated titleICCL


  • IR-98419
  • METIS-313578
  • Intermodal transportation
  • Transportation planning
  • Consolidation
  • Time horizon
  • Approximate dynamic programming


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