Railway Capacity Allocation Modeling Using a Genetic Algorithm

2017 ◽  
Vol 2608 (1) ◽  
pp. 115-124
Author(s):  
Hyunseung Kim ◽  
In-Jae Jeong ◽  
Dongjoo Park
Keyword(s):  
Genetic Algorithm ◽  
South Korea ◽  
High Speed ◽  
Rational Solution ◽  
Capacity Allocation ◽  
High Speed Railway ◽  
South Korean ◽  
Transport Services ◽  
Proposed Model ◽  
Railway Capacity

The South Korean government has established guidelines for railway capacity allocation. Railway transport services are provided by a monopoly company, which together with the guidelines, has hampered research into railway capacity allocation in South Korea. Recently, a new high-speed railway company has been established. Therefore, there is a pressing need for a fair and objective railway capacity allocation procedure. A model was developed to be applicable to South Korean high-speed railway capacity allocation, which is optimized by viewing the railway network as a location–time network. Because railway capacity allocation in South Korea is an administered process, various requirements must be followed; the model uses a genetic algorithm for such requirements. Two test scenarios were used to validate the proposed model, the solution to which resolves more than 70% of conflicts within 20 iterations (148 min). When an attempt is made to schedule infeasible trains compulsively, it is impossible to do so without relaxing one or more constraints. The average headway among real operating trains is very close to the results of the analysis. The proposed model with a genetic algorithm is a rational solution.

Crew Planning Optimization Model of High-Speed Railway

2013 ◽  
Vol 869-870 ◽  
pp. 298-304 ◽  
Author(s):  
Jin Mei Li ◽  
Lei Nie
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Set Covering ◽  
High Speed Railway ◽  
Planning Optimization ◽  
Proposed Model ◽  
Phase Setting ◽  
Crew Planning ◽  
Covering Model

Crew planning with complicated constraints is decomposed into two sequential phases: crew scheduling phase, crew rostering phase. Setting a dynamic model based on set covering model, Genetic Algorithm is adopted based on feasible solution range in search of optimal scheduling set with minimum time. Constructing a node-arc TSP network, it adopts Genetic Algorithm and Simulated Annealing Algorithm to create a work roster. Based on Wuhan-Guangzhou High-Speed Railway in China, the balance degree of crew planning is measured by crew working time entropy. The proposed model proves strong practical application.

scholarly journals The Impact of High-Speed Railways on Unequal Accessibility Based on Ticket Prices in Korea

2020 ◽  
Vol 12 (16) ◽  
pp. 6302
Author(s):  
Kyungtaek Kim ◽  
Junghoon Kim
Keyword(s):  
Urban Population ◽  
High Speed ◽  
National Level ◽  
High Speed Railway ◽  
Large Cities ◽  
South Korean ◽  
Time Value ◽  
Population Sizes ◽  
Ticket Prices ◽  
The Impact

The high-speed railway (HSR) has affected accessibility at diverse spatial levels. Although previous studies have examined HSR impacts on accessibility and inequality, the price attribute in estimating accessibility is less noted. This study evaluates the effects of HSR on unequal accessibility at the South Korean national level, capital and non-capital regions and according to urban population sizes by comparing ticket prices to time values. There are two major conclusions of this study. First, an increase in time value through national growth or other exogenous conditions maximizes HSR impact and, thus, increases accessibility. For example, when the time value is 9.98 USD/h, the national HSR access inequality is reduced by 0.56%. However, when the time value is 6.02 USD/h, the reduction in the national inequality by the HSR is 0.19%. Second, if considering generalized travel time, HSR impact is maximized in medium cities rather than in large cities. When the time value is 6.02 USD/h (or 9.98 USD/h), the change in inequality between cities is −0.4% (−1.29%) in medium cities, while large cities show a −0.08% (−0.9%) reduction in access inequality.

scholarly journals Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yun Wang ◽  
Yu Zhou ◽  
Xuedong Yan
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Sustainable Transportation ◽  
Utilization Efficiency ◽  
Practical Significance ◽  
Railway Transportation ◽  
High Speed Railway ◽  
Utilization Scheme ◽  
The One ◽  
New Research

As a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China. With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot. Moreover, the emergence of railway transportation hubs has brought great challenges to the traditional train-sets’ utilization mode. Thus, in this paper, we address the issue of train-sets’ utilization problem with the consideration of railway transportation hubs, which consists of finding an optimal Train-set Circulation Plan (TCP) to complete trip tasks in a given Train Diagram (TD). An integer programming TCP model is established to optimize the train-set utilization scheme, aiming to obtain the one-to-one correspondence relationship among sets of train-sets, trip tasks, and maintenances. A genetic algorithm (GA) is designed to solve the model. A case study based on Nanjing and Shanghai HSR transportation hubs is made to demonstrate the practical significance of the proposed method. The results show that a more efficient TCP can be formulated by introducing train-sets being dispatched among different stations in the same hub.

scholarly journals Optimization of Train Trip Package Operation Scheme

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Lu Tong ◽  
Lei Nie ◽  
Zhenhuan He ◽  
Huiling Fu
Keyword(s):  
Genetic Algorithm ◽  
Large Volume ◽  
High Speed ◽  
Freight Transportation ◽  
Fixed Time ◽  
Long Distance ◽  
Related Factors ◽  
Railway Freight ◽  
Proposed Model ◽  
Fixed Path

Train trip package transportation is an advanced form of railway freight transportation, realized by a specialized train which has fixed stations, fixed time, and fixed path. Train trip package transportation has lots of advantages, such as large volume, long distance, high speed, simple forms of organization, and high margin, so it has become the main way of railway freight transportation. This paper firstly analyzes the related factors of train trip package transportation from its organizational forms and characteristics. Then an optimization model for train trip package transportation is established to provide optimum operation schemes. The proposed model is solved by the genetic algorithm. At last, the paper tests the model on the basis of the data of 8 regions. The results show that the proposed method is feasible for solving operation scheme issues of train trip package.

scholarly journals Chinese High-speed Railway: Efficiency Comparison and the Future

2019 ◽  
Vol 31 (6) ◽  
pp. 693-702 ◽  
Author(s):  
Weidong Li ◽  
Olli-Pekka Hilmola ◽  
Jianhong Wu
Keyword(s):  
High Speed ◽  
Diffusion Models ◽  
High Speed Railway ◽  
Expansion Phase ◽  
South Korean ◽  
Network Building ◽  
Network Investment ◽  
Dea Efficiency ◽  
Efficiency Comparison ◽  
Frontier Efficiency

High-speed railway (HSR) network building was initiated in China in the early 2000s, and full-scale construction began several years later as a larger use phase started in 2008. Thereafter, the expansion speed has been impressive. Network investment could be considered as a success, if evaluating the amount of high-speed railway usage already during the expansion phase. The diffusion models built in this research show that expansion in the network and growth of the passengers will continue at least until the following decade. The performance is evaluated in terms of DEA efficiency model. It is shown that efficiency started from very low levels, but it has been increasing together with the expansion of HSR network. Currently, the efficiency is near the level of the leading European High-speed (HS) countries (Germany and France). However, it is projected with linear model and by Bass diffusion models that the efficiency will reach Japanese and South Korean standards in the next decade. A somewhat larger network length with smaller relative growth of passengers, but with a higher growth of passenger-km seems to be able to reach even the frontier efficiency.

scholarly journals A Discrete-Space Train Movement Model for a High-Speed Train under Temporary Speed Restriction

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Sihui Long ◽  
Lingyun Meng ◽  
Yihui Wang ◽  
Jianrui Miao ◽  
Xuan Li
Keyword(s):  
High Speed ◽  
Discrete Space ◽  
High Speed Train ◽  
Time Duration ◽  
Movement Model ◽  
High Speed Railway ◽  
Running Time ◽  
Proposed Model ◽  
The Impact ◽  
Block Section

This paper constructs a discrete-space train movement model to evaluate the impact of a temporary speed restriction (TSR) for a high-speed railway train. The established model can demonstrate train movement under different TSR conditions. The proposed model can reveal whether a train is affected by the block section influenced by the TSR within a time duration. Moreover, the model can output detailed train trajectories and the minimal train running time between two adjacent stations to analyse the impact of the TSR. Based on the experimental results, we carry out a comprehensive analysis of the impact of several factors on the running time and train trajectories, including the length of the affected area (i.e., number of affected block sections), the location of the TSR, the limited speed value, and the stopping patterns of the train at two adjacent stations. The experiments show that the proposed discrete-space train movement model can be used to analyse the impact of the TSR on a high-speed railway train under various considered TSR conditions.

scholarly journals Track Allocation Optimization in Multi-Direction High-Speed Railway Stations

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 459 ◽  
Author(s):  
Qin Zhang ◽  
Xiaoning Zhu ◽  
Li Wang
Keyword(s):  
High Speed ◽  
Occupation Time ◽  
Rolling Stock ◽  
High Speed Rail ◽  
High Speed Railway ◽  
Railway Stations ◽  
Proposed Model ◽  
Flexible Track ◽  
Integer Linear Model ◽  
Commercial Solver

Track allocation optimization in railway stations is one of the most fundamental problems for scheduling trains, especially in multi-direction high-speed railway stations. With the construction of high-speed rail networks, this kind of station has become increasingly common. However, the track allocation depends not only on the station tracks, train timetable, and rolling stock plan, but also on the resources in the station throat area. As a result, an effective track allocation plan becomes significant but also difficult. In this paper, we consider all these factors to make the results more practicable and an integer linear model that minimizes the total occupation time of resources in the throat area is presented. A flexible track utilization rule is also adopted to this model to fit the characteristics of the multi-direction station. Meanwhile, a detailed explanation of resources’ occupation time is illustrated to facilitate the representation of the conflicting constraints. To resolve these issues, we use a commercial solver with its default parameters. A computational experiment of a station is conducted to verify the effectiveness of the proposed model. The resources utilization plan indicates that the capacity of a station is limited by the throat area, rather than by the station tracks.

scholarly journals Passenger-to-Car Assignment Optimization Model for High-Speed Railway with Risk of COVID-19 Transmission Consideration

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiaqi Zeng ◽  
Dianhai Wang ◽  
Guozheng Zhang ◽  
Yi Yu ◽  
Zhengyi Cai
Keyword(s):  
Disease Transmission ◽  
High Speed ◽  
Infection Risk ◽  
Low Flow ◽  
Base Case ◽  
High Speed Railway ◽  
Contagious Diseases ◽  
Proposed Model ◽  
Integer Quadratic Programming ◽  
Risk Areas

Narrow and closed spaces like high-speed train cabins are at great risk for airborne infectious disease transmission. With the threat of COVID-19 as well as other potential contagious diseases, it is necessary to protect passengers from infection. Except for the traditional preventions such as increasing ventilation or wearing masks, this paper proposes a novel measurement that optimizes passenger-to-car assignment schemes to reduce the infection risk for high-speed railway passengers. First, we estimated the probability of an infected person boarding the train at any station. Once infectors occur, the non-steady-state Wells–Riley equation is used to model the airborne transmission intercar cabin. The expected number of susceptible passengers infected on the train can be calculated, which is the so-called overall infection risk. The model to minimize overall infection risk, as a pure integer quadratic programming problem, is solved by LINGO software and tested on several scenarios compared with the classical sequential and discrete assignment strategies used in China. The results show that the proposed model can reduce 67.6% and 56.8% of the infection risk in the base case compared to the sequential and discrete assignment, respectively. In other scenarios, the reduction lies mostly between 10% and 90%. The optimized assignment scheme suggests that the cotravel itinerary among passengers from high-risk and low-risk areas should be reduced, as well as passengers with long- and short-distance trips. Sensitivity analysis shows that our model works better when the incidence is higher at downstream or low-flow stations. Increasing the number of cars and car service capacity can also improve the optimization effect. Moreover, the model is applicable to other epidemics since it is insensitive to the Wells–Riley equation parameters. The results can provide a guideline for railway operators during the post-COVID-19 and other epidemic periods.

Sign in / Sign up

Export Citation Format

Share Document