scholarly journals An Optimization Method for the Train Service Network Design Problem

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Jie Xiao ◽  
Yi Xie ◽  
Haowei Yu ◽  
Hongying Yan

Effective railway freight transportation relies on a well-designed train service network. This paper investigates the train service network design problem at the tactical level for the Chinese railway system. It aims to determine the types of train services to be offered, how many trains of each service are to be dispatched per day (service frequency), and by which train services shipments are to be transported. An integer programming model is proposed to address this problem. The optimization model considers both through train services between nonadjacent yards, and two classes of service between two adjacent yards ( i.e., shuttle train services directly from one yard to its adjacent yard, and local train services that make at least one intermediate stop). The objective of the model is to optimize the transportation of all the shipments with minimal costs. The costs consist of accumulation costs, classification coststrain operation costs, and train travel costs. The NP-hard nature of the problem prevents an exact solution algorithm from finding the optimal solution within a reasonable time, even for small-scale cases. Therefore, an improved genetic algorithm is designed and employed here. To demonstrate the proposed model and the algorithm, a case study on a real-world sub-network in China is carried out. The computational results show that the proposed approach can obtain high-quality solutions with satisfactory speed. Moreover, comparative analysis on a case that assumes all the shuttle train services between any two adjacent yards to be provided without optimization reveals some interesting insights.

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 391 ◽  
Author(s):  
Siqi Liu ◽  
Boliang Lin ◽  
Jianping Wu ◽  
Yinan Zhao

As air pollution becomes increasingly severe, express trains play a more important role in shifting road freight and reducing carbon emissions. Thus, the design of railway express shipment service networks has become a key issue, which needs to be addressed urgently both in theory and practice. The railway express shipment service network design problem (RESSNDP) not only involves the selection of train services and determination of service frequency, but it is also associated with shipment routing, which can be viewed as a service network design problem (SNDP) with railway characteristics. This paper proposes a non-linear integer programming model (INLP) which aims at finding a service network and shipment routing plan with minimum cost while satisfying the transportation time constraints of shipments, carrying capacity constraints of train services, flow conservation constraint and logical constraints among decision variables. In addition, a linearization technique was adopted to transform our model into a linear one to obtain a global optimal solution. To evaluate the effectiveness and efficiency of our approach, a small trial problem was solved by the state-of-the-art mathematical programming solver Gurobi 7.5.2.


Symmetry ◽  
2018 ◽  
Vol 10 (6) ◽  
pp. 227 ◽  
Author(s):  
Boliang Lin ◽  
Jianping Wu ◽  
Jiaxi Wang ◽  
Jingsong Duan ◽  
Yinan Zhao

2020 ◽  
Vol 141 ◽  
pp. 164-195
Author(s):  
Yannick Oskar Scherr ◽  
Mike Hewitt ◽  
Bruno Albert Neumann Saavedra ◽  
Dirk Christian Mattfeld

2017 ◽  
Vol 65 (5) ◽  
pp. 1303-1321 ◽  
Author(s):  
Natashia Boland ◽  
Mike Hewitt ◽  
Luke Marshall ◽  
Martin Savelsbergh

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Yi Zhao ◽  
Qingwan Xue ◽  
Zhichao Cao ◽  
Xi Zhang

Compared with traditional freight transportation, intermodal freight transportation is more competitive which can combine the advantages of different transportation modes. As a consequence, operational research on intermodal freight transportation has received more attention and developed rapidly, but it is still a young research field. In this paper, a stochastic intermodal service network design problem is introduced in a sea-rail transportation system, which considers stochastic travel time, stochastic transfer time, and stochastic container demand. Given candidate train and ship services, we develop a two-stage chance constrained programming model for this problem with the objective of minimising the expected total cost. The first stage allows for the selection of operated services, while the second stage focuses on the determination of intermodal container routes where capacity and on-time delivery chance constraints are presented. A hybrid heuristic algorithm, incorporating sample average approximation and ant colony optimisation, is employed to solve this model. The proposed model is applied to a realistic intermodal sea-rail network, which demonstrates the performance of the model and algorithm as well as the influence of stochasticity on transportation plans. Hence, the proposed methodology can improve effectively the performance of intermodal service network design scheme under stochastic conditions and provide managerial insights for decision-makers.


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