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

Title: Increasing the Capacity of Shunting Yards Within the Current Infrastructure: A Computational Perspective
Authors: Hanou, Issa K.; Dumančić, Sebastijan; de Weerdt, Mathijs; Voort, Paul van der; Broek, Roel van den; Akker, Marjan van den; Sub Simulation of Complex Systems
Publication Year: 2026
Subject Terms: abstractions; human-AI collaboration; hybrid model; neuro-symbolic AI; railway hub; train servicing; train shunting; Control and Systems Engineering; Automotive Engineering; Transportation; Energy (miscellaneous)
Description: 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.
Document Type: book part
File Description: application/pdf
Language: English
ISSN: 2196-5544
Relation: https://dspace.library.uu.nl/handle/1874/483149
Availability: https://dspace.library.uu.nl/handle/1874/483149
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.7FE9FDA
Database: BASE