Combinatorial and Robust Optimisation Models and Algorithms for Railway Applications

Galli, Laura (2009) Combinatorial and Robust Optimisation Models and Algorithms for Railway Applications, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Automatica e ricerca operativa, 21 Ciclo. DOI 10.6092/unibo/amsdottorato/1514.
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This thesis deals with an investigation of combinatorial and robust optimisation models to solve railway problems. Railway applications represent a challenging area for operations research. In fact, most problems in this context can be modelled as combinatorial optimisation problems, in which the number of feasible solutions is finite. Yet, despite the astonishing success in the field of combinatorial optimisation, the current state of algorithmic research faces severe difficulties with highly-complex and data-intensive applications such as those dealing with optimisation issues in large-scale transportation networks. One of the main issues concerns imperfect information. The idea of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, dates back to 1970s. Unfortunately, none of those techniques proved to be successfully applicable in one of the most complex and largest in scale (transportation) settings: that of railway systems. Railway optimisation deals with planning and scheduling problems over several time horizons. Disturbances are inevitable and severely affect the planning process. Here we focus on two compelling aspects of planning: robust planning and online (real-time) planning.

Tipologia del documento
Tesi di dottorato
Galli, Laura
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Settore disciplinare
Settore concorsuale
Parole chiave
Combinatorial Optimisation, Integer Programming, 0-1 Quadratic Programming, Train Platforming, Robust Optimisation, Recoverable Robustness, Network Buffering, Online Planning, Rescheduling, Rolling Stock Planning
Data di discussione
16 Aprile 2009

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