Reducing driver movements in railway rescheduling by optimising a multi-commodity network flow model with a variable neighbourhood search

This thesis aims to reduce taxi costs by rescheduling the short-term planning of DB Cargo. This is accomplished by optimising the short-term plan and evaluating company car scheduling strategies. The rescheduling problem is represented on a Multi-Commodity Network Flow Model. The short-term plan is optimised using a Variable Neighbourhood Search, which reduces the required driver movements. Based on the optimised planning, company car scheduling strategies are evaluated. The reduction of required driver movements, combined with the optimisation of company car scheduling, results in a reduction in taxi usage.