The railway network design problem is one of the critical issues in the transportation sector due to its significance and variety of necessary applications. The major issue of this field relates to the decision of whether to increase the railways’ capacity or construct a new route to meet demand. Although the budget is a great concern of the managers for making such a decision, environmental factors should be necessarily included in the decision-making process. Therefore, this research proposes a novel robust bi-objective mixed-integer linear programming (MILP) model to simultaneously minimize the total cost and environmental impact under uncertain conditions and within a given time horizon. The proposed problem addresses strategic and operational decisions through railway project selection and product flow determination. To deal with the bi-objectiveness of the model and tackle the complexity of the problem, a nondominated sorting genetic algorithm (NSGA-II) is employed. The proposed NSGA-II could reach near-optimal Pareto solutions in a reasonable solution time and showed a reliable performance for being employed in large-sized instances. It also indicates that the proposed NSGA-II can be utilized for solving large-sized samples in a very short time.