textRailway rolling stock (locomotives, carriages, and train units) is one
of the most significant cost sources for operatorsof passenger trains,
both public and private. Rolling stock costsare due to material
acquisition, power supply, and material maintenance. The efficient
circulation of rolling stock material is therefore one of the
objectives pursued. In this paper we focus on the circulation of train
units on a single line. In order to utilize the train units on this
line in an efficient way, they are added to or removed from the trains
in certain stations, according to the passengers' seat demand. Since
adding and removing train units has to respect specific rules, it is
important to know the exact order of the train units in the trains.
This aspect strongly increases the complexity of the rolling stock
circulation problem. In this paper we present aninteger programming
approach to solve this problem. We also apply this approach to a real
life case study based on the 2001-2002 timetable of NS Reizigers, the
major Dutch operator of passenger trains.

Efficient Circulation of Railway Rolling Stock

Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line

ABSTRACT The line between fantasy and reality has become blurred in online gaming, whereby tourists are willing to visit associated real-world destinations they have experienced within virtual worlds (e.g. online games). This study investigates the impact of gamers’ interactions with non-player characters (NPCs) and other gamers on their in-game emotional solidarity, destination image and willingness to visit associated real-world destinations. Data were collected from 538 Grand Theft Auto 5 gamers and analysed using covariance-based structural equation modelling (CB-SEM). Results reveal that both gamer-NPCs and gamer-gamer interactions were positively associated with emotional solidarity with NPCs and gamers, respectively. Also, emotional solidarity with NPCs and emotional solidarity with gamers were positively associated with in-game cognitive image. The in-game cognitive image was further confirmed to be positively associated with affective image and conative image. The in-game conative image was confirmed to be positively associated with the willingness to visit associated real-world destinations. These findings make a novel contribution to the literature on online gaming and tourism. Game developers need to develop activities that promote interactions between gamers while also designing NPCs that resemble locals and their customs to facilitate increased visitation to real-world destinations.

/pdf/from-virtual-to-actual-destinations-do-interactions-with-2x49ky2a.pdf

From virtual to actual destinations: do interactions with others, emotional solidarity, and destination image in online games influence willingness to travel?

A Distributionally Robust Optimization Method for Passenger Flow Control Strategy and Train Scheduling on an Urban Rail Transit Line

In metro system, the fault of traction power supply system may cause the power supply shortage around the failure substation. In this case, the dispatching measure should be immediately taken to reduce the impacts of disruption on the train operation. To deal with this real-time traffic management problem, a cooperative control approach is proposed in this paper. In this approach, the time to apply tractive force and the level of force are simultaneously adjusted for all the operated trains, to maximize the maintained line capacity when considering the power supply capacity. Compared with the existing train timetable rescheduling approach, cooperative control is more flexible to get a better train regulation solution. To solve the challenges for developing the cooperative control model (i.e., undetermined number and dynamically changing of controlled objects), an imaginary section method is newly developed to transform the original problem into an equivalent cooperative control problem with fixed controlled objects. Then, the mathematical models for the transformed problem are constructed by using the space–time–speed network methodology. According to the formulated model, a Decentralized-Markov Decision Process (Dec-MDP) framework is designed as the basis of the applied algorithm. Next, a Collaboration Mechanism Based-Independent Deep Q-Network (CMB-IDQN) algorithm is proposed to solve the cooperative control problem. Compared with classical IDQN algorithm, a credit assignment method based on the collaboration mechanism among trains is novelly considered in the designed multi-agent reinforcement learning algorithm. Finally, the effectiveness of the proposed cooperative control approach is verified by two case studies. When solving the cooperative control problem, the performance by using CMB-IDQN algorithm can be increased by up to 13.0% and 16.8% compared with other two classical reinforcement learning algorithms (i.e., DQN and IDQN), respectively. Compared with two train timetable rescheduling measures during the power supply shortage, the cooperative control approach can improve the solution quality by more than 180.4% and 17.4%, respectively. 

Cooperative train control during the power supply shortage in metro system: A multi-agent reinforcement learning approach

Subway lines connecting different urban functional zones in large cities have direction-dependent and time-variant passenger demand, namely, asymmetry in passenger demand. Most existing studies adopt a symmetric strategy to design operations in both directions and sequentially optimize the different problems associated with operations, thereby failing to meet the asymmetry in passenger demand. This study formulates an asymmetric operation strategy as an integrated mixed-integer non-linear model to optimize the entire operational process of rolling stock from the perspective of service quality and operating costs. Based on the proposed model, an exact algorithm is proposed with speed-up techniques to quickly generate an optimal solution. To this end, the original model is decomposed into several sub-problems that can be exactly solved by using a forward dynamic programming algorithm. Based on actual data from the Beijing subway's Yizhuang line, numerical experiments are conducted to investigate the effectiveness of the asymmetric operation strategy, to identify managerial insights on the integrated optimization, and to evaluate the performance of the proposed methodology.

/pdf/an-exact-method-for-the-integrated-optimization-of-subway-1zhpaiblu7.pdf

An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs

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An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs