Abstract
In recent times, the effective management of rail fleet planning issues in transportation networks has gained immense importance in ensuring the financial viability of rail freight transportation operations. Unfortunately, several rail freight operators have been hindered in developing effective models due to the dearth of appropriate tools and methodologies. This, in turn, has posed significant challenges for planners who strive to optimize the transportation of manufactured products from diverse manufacturing plants to market destinations. To surmount the difficulties faced, a decision-support model is proposed in this research. The model employs a mathematical optimization technique known as mixed-integer linear programming (MILP) to determine the optimum combination of plant and customer pairs, the ideal number of trips between the pairs, and the maximum quantity of goods that can be transported. The MILP model is solved using an exact approach, enabling rail freight operators to pinpoint profitable routes, schedule their rakes to maximize freight trips, and guarantee efficient, competitive, and secure rail freight services. The primary aim of this study is to maximize the number of freight trips, as it has an immediate effect on the profitability of rail freight operators. Furthermore, this model can assist rail freight operators in managing costs and identifying new market opportunities, contributing to the long-term success and sustainability of their operations.
