Energy Optimization Models for the Locomotive Assignment Problem

ABSTRACT Reducing energy consumption is a key objective in transportation. Using detailed infrastructure data, this study introduces the Green Locomotive Assignment Problem (GLAP) to minimize energy consumption in railway operations by efficiently assigning locomotives to pre‐scheduled trains. The model targets key energy consumption sources, such as heating, consist‐busting, idling, and light‐traveling, which occurs when locomotives relocate without pulling a train. Energy consumption and regenerative braking during light‐traveling are calculated using the Davis equation with track gradients. Additionally, we propose a variation of the model that incorporates deadheading, where locomotives are repositioned by attaching them to trains without fully using their engines. Including detailed gradient information from the Austrian railway network, we compare the distance‐ and locomotive‐minimizing objective with the GLAP solution and observe that energy consumption can be reduced significantly by utilizing more energy‐efficient paths, and optimizing the order of locomotive types on light‐traveling trips.