Show simple item record

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorHoogeveen, Han
dc.contributor.authorBerg, Sander van den
dc.date.accessioned2025-08-15T00:02:27Z
dc.date.available2025-08-15T00:02:27Z
dc.date.issued2025
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/49736
dc.description.abstractThe Nederlandse Spoorwegen (NS) is the largest passenger railway operator in the Netherlands and operates a fleet of more than 700 train units. One of the problems they encounter in their planning process is the Rolling Stock Scheduling Problem, which involves the assignment of compositions to a set of pre-existing trips. The goal is to find composition assignments that minimize the number of passengers that cannot be seated, while also taking into account other costs. In this thesis, we will show a way to approach this problem using a local search heuristic. An additional challenge in this is the planning of night movements to allow for a more efficient usage of the available train units. We propose a flow approach to solve this subproblem, which we then expand to an MIP that can be solved during steps of the local search. We compare our results with those of TAM, a solver that is currently used to find solutions to the problem using a MIP. Using this we are able to find solutions that are 5-10\% off the TAM benchmark in most scenarios.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectRolling Stock Scheduling in an integrated planning process
dc.titleRolling Stock Scheduling in an integrated planning process
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsRolling Stock Scheduling ; Local Search ; Simulated Annealing ; Train Scheduling ;
dc.subject.courseuuComputing Science
dc.thesis.id51658


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record