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Energy saving has become a key concern of metro systems to reduce operating costs and meet the requirements of sustainable development. Energy-efficient timetabling, an effective way to reduce traction energy consumption, has gotten much attention in recent decades. However, limited research about energy-efficient timetabling simultaneously considered realistic speed profiles and the influence of train loads, which change greatly in different sections and significantly affect energy consumption. Therefore, this paper proposes an energy-efficient timetabling approach to improve regenerative energy utilization based on varying train loads and realistic speed profiles for bidirectional metro lines. First, based on the operational and safety constraints, this paper constructs an integer energy-efficient timetabling model where dwell times and nonuniform headways are taken as decision variables. Besides, the turnaround process is also considered to ensure rolling stock circulation efficiency. Sectional passenger volumes are employed to determine the varying train loads. Energy consumption is calculated based on realistic speed profiles. Owing to the complexity of the model, an improved adaptive large neighborhood search (ALNS) algorithm is designed to solve this model according to its characteristics. Finally, numerical examples are conducted based on the practical data from Shanghai Metro Line 17. The results indicate that the proposed approach effectively solves the energy-efficient timetabling problem with varying train loads and realistic speed profiles for bi-directional metro lines. The approach is suitable for off peak hours and can reduce energy consumption effectively, and the reduction is up to 11.9% for the presented cases. The improved ALNS algorithm can find good solutions within reasonable times in different cases. Moreover, compared with the widely used genetic algorithm in the literature, the improved ALNS algorithm is more efficient in solving the proposed energy-efficient timetabling problem in different cases. [ABSTRACT FROM AUTHOR]

• The net CO2 emissions of the Beijing-Shanghai high-speed rail are assessed. • The framework incorporates modal substitution and traffic generation effects. • Avoided infrastructure expansion and vehicle manufacturing are considered. • Large share of traffic diverted from ordinary-speed trains may raise emissions. This paper provides an ex-post assessment of net carbon dioxide (CO2) emissions of the Beijing-Shanghai high-speed rail (HSR) by including both mode substitution and traffic generation effects with a life-cycle approach. We are among the first authors to examine the emissions effects of a long-haul HSR and to consider the effects of avoided infrastructure expansion and vehicle manufacturing due to traffic diversion. We find that avoided infrastructure expansion plays a limited role in offsetting CO2 emissions from the construction of an HSR infrastructure, but the reduced demand for passenger vehicles can offset a larger share of emissions from the manufacturing of HSR rolling stock. Initially, too much traffic was diverted from ordinary-speed rail (OSR) to HSR, increasing emissions at the operation stage. As traffic diverted from road and air increased, the net emissions at the operation stage turned negative, offsetting emissions from infrastructure construction and vehicle manufacturing. [ABSTRACT FROM AUTHOR]

• A method to solve train rescheduling and passenger reassignment simultaneously. • An integrated optimization model is formulated with a bi-objective function. • Our method can facilitate real-time rescheduling and re-ticketing efficiently. • Non-dominated train rescheduling and passenger reassignment solutions are obtained. During railway operations, unexpected events may influence normal traffic flows. This paper focuses on a train rescheduling problem for handling large disruptions, such as a rolling stock breakdown leading to a cancelled train service, where passenger reassignment strategies have to be considered. A novel mixed-integer linear programming formulation is established with consideration of train retiming, reordering, rerouting, and reservicing (addition of extra stops). The proposed mathematical formulation considers planning extra stops for non-canceled trains in order to transport the disrupted passengers, which were supposed to travel on the canceled train, to their pre-planned destination stations. Other constraints deal with limited seat capacity and track capacity, and mapping train rescheduling with passenger reassignment. A bi-objective function is optimized by a weighted-sum method to maximize the number of disrupted passengers reaching their destination stations and to minimize the weighted total train delay for all non-canceled trains at their destinations. A series of numerical experiments based on a part of the Beijing-Shanghai high-speed railway line is carried out to verify the effectiveness and efficiency of the proposed model and to perform a sensitivity analysis of various performance factors. The results show that an optimal reassignment plan of disrupted passengers is important to achieve real-time efficiency of traffic and re-ticketing. The impact of passenger reassignment on train rescheduling is influenced by the weights for objectives, duration of disruption, allowed additional dwell and running times, and relationship between passenger demand and total available train capacity. [ABSTRACT FROM AUTHOR]