Speed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

速度是能源消耗和列车调度问题中最有影响的变量之一。提高速度可以保证准点，从而提高铁路运力和铁路利益相关者的满意度和收入。然而，速度的提高会导致更多的能源消耗和成本，从而导致更多的污染物排放。因此，确定经济速度需要在用户的期望和铁路系统提供牵引力以克服由于铁路路线和移动条件引起的运行阻力之间进行权衡，是铁路研究中的一个关键挑战。本文提出了一种新的模糊多目标模型，该模型通过整合微观和宏观层面，确定区间段列车的经济速度，可以优化列车行驶时间和能源消耗。在具有不同列车调度场景的实际案例中实施所提出的模型表明，该模型可以在不改变能耗比的情况下将总行程时间提高 19%。所提出的模型几乎不需要专家意见的输入来确定速率和参数。