Optimal Allocation of Physical Assets in the Railway Sector

This Thesis analyzes the class of planning and scheduling problems generally named Locomotive Assignment Problem (LAP) and proposes a methodological innovation in the solution of this class of problems. The first part of the Thesis presents a comprehensive survey of the optimization models developed to solve the LAP. This class of problems, that were historically solved by simulation, can now be solved using mathematical optimization techniques. Large-scale very complex freight rail activities impose to separate the LAP in three distinct phases. Namely we have to solve the Locomotive Planning Problem (LPP), the Locomotive Scheduling Problem (LSP), and finally the Locomotive Routing Problem (LRP) in which the refueling of diesel locomotives has to be guaranteed. The separation of the LAP leads to definitely suboptimal solutions. However, a structural integration of these three phases in a model that encompasses the LPP, the LSP and the LRP is prohibitive for real problems. The aim of the second part of this Thesis is to introduce a methodological innovation able to (partially) integrate the planning and the routing of consists (groups of linked locomotives that provides the required motive power performance). Our objective is to obtain LPP solutions that make the routing phase easier to handle and more economical. We pursue this objective first considering the LPP in its Consists Flow Formulation, and second exploiting information on consists range and fuel capacity exploitation not featured in the previous studies. This study proposes an integer optimization model named Consists Selection that identifies the set C of consists types (available to solve the LPP) maximizing the consist range and the consist efficiency in the fuel tank capacity exploitation. The last part of the Thesis describes the creation of simulation program able to generate realistic train schedules.