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While solving the shunting scheduling of EMU first-level maintenance (SSEFM), most existing literature assumed a single maintenance route for all trains and considered only a through depot. It neglects the problem-specific characteristics in terms of varied maintenance routes and a stub-end depot, causing the infeasibility of the generated schedule in such particular circumstances. Therefore, the SSEFM problem with flexible maintenance routes in a stub-end depot with a transversal yard configuration is considered in this work. First, a multi-objective mixed-integer linear programming (MILP) model is formulated to maximize the reservation time in the storage area, and minimize the overstay time in the cleaning and inspecting areas. The relationship between constraints including flexible maintenance routes, train shunting conflicts, track occupation conflicts, and train arrival/departure times, are coordinated. Subsequently, a heuristic-based enhanced particle swarm optimization algorithm (EPSO) with two improvements is proposed to tackle this NP-hard problem. Specifically, three heuristic rules about the depth-first operation track allocation, the conflict-free bottleneck track allocation, and the right-shift track occupancy repair are designed to ensure the feasibility of the shunting schedule. Accordingly, a three-level decoding mechanism is designed to achieve a near-optimal shunting schedule with great train and route sequences. Two improvements on crossover and mutation operators are developed to enhance the exploration and exploitation ability. Finally, a real-world instance in China is solved to verify the effectiveness and efficiency of the proposed model and algorithm. Experimental results show that EPSO is relatively more effective than all the compared algorithms. [ABSTRACT FROM AUTHOR]

This study quantifies the absolute sea level (ASL) change along the coast of China from 1993 to 2019 using tide gauge (TG) and Global Navigation Satellite System (GNSS) data. The sea level change at 12 collocated TG and GNSS stations along the Chinese coast are first analyzed by TG + GNSS data. Then the ASL rise and its spatial variation along the coast of China and that in surrounding oceans are studied using TG + GNSS data and satellite altimetry products. The results show that the relative sea level rise along the Chinese coast varied from 2.61 ± 0.76 to 5.56 ± 0.70 mm/yr, while the effect of vertical land motion (VLM) ranged from −1.46 ± 0.30 to 1.07 ± 0.38 mm/yr. After correcting the effect of the VLM, the ASL rise ranged from 2.51 ± 0.86 to 5.03 ± 0.60 mm/yr, with a mean rate of 3.94 ± 0.88 mm/yr, which was 0.7 mm/yr higher than the global average. It is found that ASL rise rate is significantly higher in Chinese seas and neighboring oceans, with a meridional distribution in the East China Sea and a zonal distribution in the South China Sea. This may be related to factors such as sea surface temperature rise, atmospheric pressure decrease, freshwater runoff, zonal wind stress anomaly, and alongshore currents in the area. Plain Language Summary: As a consequence of climate change, the global mean sea level from tide gauges and satellite altimetry observations increased from 1.4 mm/yr over the period 1901–1990 to 3.2 mm/yr over the period 1993–2015 to 3.6 mm/yr over the period 2006–2015. An improved understanding of sea level rise is essential for the safety of society, the economy and the environment. This study quantifies the absolute sea level (ASL) change along the coast of China from 1993 to 2019 using tide gauge data with the vertical land motion corrected by Global Navigation Satellite System data. The derived ASL rise rate ranged from 2.51 ± 0.86 to 5.03 ± 0.60 mm/yr, with a mean rate of 3.94 ± 0.88 mm/yr, which was 0.7 mm/yr higher than the global average. It is also found that the ASL rise rate in Chinese seas and neighboring oceans is significantly higher than the global average, with a meridional distribution in the East China Sea and a zonal distribution in the South China Sea. The local influencing factors of sea level rise along the coast of China were analyzed, including the sea surface temperature rise, atmospheric pressure decrease, freshwater runoff, zonal wind stress anomaly and alongshore currents in the area. Key Points: Tide gauge and collocated Global Navigation Satellite System were first used to analyze the absolute sea level (ASL) changes along the coast of ChinaThe high ASL rise rate along the Chinese coast was a natural manifestation in all Chinese seas and neighboring oceansThe local influencing factors of sea level rise along the coast of China were preliminarily analyzed [ABSTRACT FROM AUTHOR]

Frequently occurring and unavoidable perturbations in railway systems cause a reduction in performance and even the infeasibility of the original schedule. In addition, existing related studies assume that the maintenance routes are fixed in a deterministic situation. Therefore, it is necessary to focus on robust scheduling of electric multiple units first-level maintenance with flexible maintenance routes to defend against stochastic uncertainties. Firstly, a mixed-integer linear programming model with uncertain parameters in objective functions and constraints is built for the first time. Multiple constraints are formulated to consider flexible maintenance routes, train shunting conflicts, and track occupation conflicts in a stub-end depot. A robust optimization approach is adopted to obtain a deterministic robust counterpart model with uncertainties in processing/arrival/departure times. In this model, uncertainty and reliability levels are introduced to describe and quantify the disturbance degree of processing/arrival/departure times and the allowable violation degree of resource constraints respectively. Moreover, an adaptive iterative local search is proposed by embedding heuristic rules for the initialization. The proposed algorithm includes problem-specific neighborhood structures to improve the evolutionary ability, a variable neighborhood descent method to guide and drive the search toward promising areas of the search space, and an adaptive perturbation mechanism to enable the algorithm to jump out of local optimum. Numerical results from China's railway system validate the proposed model and quantitatively demonstrate the merit of the proposed algorithm. Further analysis shows that our approach can achieve an appropriate trade-off between robustness and efficiency for various uncertainty and reliability levels. • The SSEFM problem under stochastic uncertainties is addressed. • A multi-objective MILP model with deterministic robust equivalent counterpart is defined. • An adaptive iterative local search is proposed to solve this problem. • The algorithm is enhanced with a variable neighborhood descent and adaptive perturbation. [ABSTRACT FROM AUTHOR]