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Increasing the Capacity of Shunting Yards Within the Current Infrastructure: A Computational Perspective

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Abstract

With a dense infrastructure and limited space, the opportunities for increasing the capacity of the railway network in the Netherlands are limited. One of the bottlenecks is optimally using the available space around stations and in shunting yards. Many details must be considered, increasing the complexity of the problem. Human planners can benefit from computational support to ensure efficient use of the infrastructure. We introduce a framework for positioning previous research in terms of abstractions and highlight a promising future direction: the development of a new approach that combines different methods and uses the relations between the abstractions to create more efficient solutions.

Original languageEnglish
Title of host publicationTRAconference 2024
EditorsGereon Meyer
PublisherSpringer Nature
Pages534-540
Number of pages7
ISBN (Electronic)2196-5552
ISBN (Print)2196-5544
DOIs
Publication statusPublished - 2025

Publication series

NameLecture Notes in Mobility
VolumePart F1004
ISSN (Print)2196-5544
ISSN (Electronic)2196-5552

Keywords

  • abstractions
  • human-AI collaboration
  • hybrid model
  • neuro-symbolic AI
  • railway hub
  • train servicing
  • train shunting

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