scholarly journals Inserting Extra Train Services on High-Speed Railway

2020 ◽  
Vol 49 (1) ◽  
pp. 16-24 ◽  
Author(s):  
Yuyan Tan ◽  
Wen Xu ◽  
Zhibin Jiang ◽  
Ziyulong Wang ◽  
Bo Sun

With the aim of supporting future traffic needs, an account of how to reconstruct an existing cyclic timetable by inserting additional train services will be given in this paper. The Timetable-based Extra Train Services Inserting (TETSI) problem is regarded as an integration of railway scheduling and rescheduling problem. The TETSI problem therefore is considered involving many constraints, such as flexible running times, dwell times, headway and time windows. Characterized based on an event-activity graph, a general Mixed Integer Program model for this problem is formulated. In addition, several extensions to the general model are further proposed. The real-world constraints that concerning the acceleration and deceleration times, priority for overtaking, allowed adjustments, periodic structure and frequency of services are incorporated into the general model. From numerical investigations using data from Shanghai-Hangzhou High-Speed Railway in China, the proposed framework and associated techniques are tested and shown to be effective.

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6610
Author(s):  
Raka Jovanovic ◽  
Islam Safak Bayram ◽  
Sertac Bayhan ◽  
Stefan Voß

Electrifying public bus transportation is a critical step in reaching net-zero goals. In this paper, the focus is on the problem of optimal scheduling of an electric bus (EB) fleet to cover a public transport timetable. The problem is modelled using a mixed integer program (MIP) in which the charging time of an EB is pertinent to the battery’s state-of-charge level. To be able to solve large problem instances corresponding to real-world applications of the model, a metaheuristic approach is investigated. To be more precise, a greedy randomized adaptive search procedure (GRASP) algorithm is developed and its performance is evaluated against optimal solutions acquired using the MIP. The GRASP algorithm is used for case studies on several public transport systems having various properties and sizes. The analysis focuses on the relation between EB ranges (battery capacity) and required charging rates (in kW) on the size of the fleet needed to cover a public transport timetable. The results of the conducted computational experiments indicate that an increase in infrastructure investment through high speed chargers can significantly decrease the size of the necessary fleets. The results also show that high speed chargers have a more significant impact than an increase in battery sizes of the EBs.


Author(s):  
Julian Hof ◽  
Michael Schneider

In numerous practical vehicle-routing applications, larger vehicles are employed as mobile depots to support a fleet of smaller vehicles that perform certain tasks. The mobile depots offer the possibility of keeping the task vehicles operational by supplying them en route with certain resources. For example, in two-echelon distribution systems, small task vehicles are used to navigate narrow streets and to deliver/collect goods or to collect waste, and larger vehicles serve as mobile depots to replenish the goods to be delivered or to receive collected goods or waste at the outskirts of the urban area. Accessibility constraints may also be imposed by regulations on emissions, which make some areas only accessible for environmentally friendly vehicles such as, for example, battery-powered electric vehicles. Especially if the respective refueling infrastructure is sparse, mobile refueling stations seem to be an interesting alternative. In this paper, we introduce the vehicle-routing problem with time windows and mobile depots (VRPTWMD) to capture the routing decisions of the described applications in a generalized fashion. The VRPTWMD is characterized by fleets of task vehicles (TVs) and support vehicles (SVs). The SVs may serve as mobile depots to restore either the load or the fuel capacity of the TVs that are used to fulfill the customer requests. We present a mixed-integer program for the VRPTWMD with which small instances can be solved using a commercial solver. Moreover, we develop a high-quality hybrid heuristic composed of an adaptive large neighborhood search and a path relinking approach to provide solutions on larger problem instances. We use a newly generated set of large VRPTWMD instances to analyze the effect of different problem characteristics on the structure of the identified solutions. In addition, our approach shows very convincing performance on benchmark instances for the related two-echelon multiple-trip VRP with satellite synchronization, which can be viewed as a special case of the VRPTWMD. Our heuristic is able to significantly improve a large part of the previous best-known solutions while spending notably less computation time than the comparison algorithm from the literature.


2019 ◽  
Vol 48 (1) ◽  
pp. 31-38
Author(s):  
Wen Xu ◽  
Yuyan Tan ◽  
Bishal Sharma ◽  
Ziyulong Wang

Due to several obvious advantages both in transport marketing and train operation planning, the cyclic timetable has already applied in many high-speed railway (HSR) countries. In order to adopt the cyclic timetable in China's HSR system, a Mixed Integer Programmer (MIP) model is proposed in this paper involving many general constraints, such as running time, dwell time, headway, and connection constraints. In addition, the real-world overtaking rule that concerning a train with higher priority will not be overtaken by a slower one is incorporated into the cyclic timetable optimization model. An approach based on fixed departure is proposed to get a cyclic timetable with minimum total journey time within a reasonable time. From numerical investigations using data from Guangzhou-Zhuhai HSR line in China, the proposed model and associated approach are tested and shown to be effective.


2016 ◽  
Vol 46 (2) ◽  
pp. 234-248 ◽  
Author(s):  
Erin J. Belval ◽  
Yu Wei ◽  
Michael Bevers

Wildfire behavior is a complex and stochastic phenomenon that can present unique tactical management challenges. This paper investigates a multistage stochastic mixed integer program with full recourse to model spatially explicit fire behavior and to select suppression locations for a wildland fire. Simplified suppression decisions take the form of “suppression nodes”, which are placed on a raster landscape for multiple decision stages. Weather scenarios are used to represent a distribution of probable changes in fire behavior in response to random weather changes, modeled using probabilistic weather trees. Multistage suppression decisions and fire behavior respond to these weather events and to each other. Nonanticipativity constraints ensure that suppression decisions account for uncertainty in weather forecasts. Test cases for this model provide examples of fire behavior interacting with suppression to achieve a minimum expected area impacted by fire and suppression.


1976 ◽  
Vol 8 (4) ◽  
pp. 443-446
Author(s):  
W G Truscott

This note examines a previously published model for dynamic location—allocation analysis. The usefulness of this model is enhanced by reformulating the problem as an operational zero-one, mixed-integer program while retaining the intent of the original version.


Author(s):  
Minling Feng ◽  
Chaoxian Wu ◽  
Shaofeng Lu ◽  
Yihui Wang

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.


Author(s):  
Elias Olivares-Benitez ◽  
Pilar Novo Ibarra ◽  
Samuel Nucamendi-Guillén ◽  
Omar G. Rojas

This chapter presents a case study to organize the sales territories for a company with 11 sales managers to be assigned to 111 sales coverage units in Mexico. The assignment problem is modeled as a mathematical program with two objective functions. One objective minimizes the maximum distance traveled by the manager, and the other objective minimizes the variation of the sales growth goals with respect to the national average. To solve the bi-objective non-linear mixed-integer program, a weights method is selected. Some instances are solved using commercial software with long computational times. Also, a heuristic and a metaheuristic based on simulated annealing were developed. The design of the heuristic generates good solutions for the distance objective. The metaheuristic produces better results than the heuristic, with a better balance between the objectives. The heuristic and the metaheuristic are capable of providing good results with short computational times.


2020 ◽  
Vol 21 (4) ◽  
pp. 1459-1486
Author(s):  
Vassilis M. Charitopoulos ◽  
Vivek Dua ◽  
Jose M. Pinto ◽  
Lazaros G. Papageorgiou

Abstract Under the ever-increasing capital intensive environment that contemporary process industries face, oligopolies begin to form in mature markets where a small number of companies regulate and serve the customer base. Strategic and operational decisions are highly dependent on the firms’ customer portfolio and conventional modelling approaches neglect the rational behaviour of the decision makers, with regards to the problem of customer allocation, by assuming either static competition or a leader-follower structure. In this article, we address the fair customer allocation within oligopolies by employing the Nash bargaining approach. The overall problem is formulated as mixed integer program with linear constraints and a nonlinear objective function which is further linearised following a separable programming approach. Case studies from the industrial liquid market highlight the importance and benefits of the proposed game theoretic approach.


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