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.

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.

A Bi-Level Passenger Preference-Oriented Line Planning Model for High-Speed Railway Operations

2018 ◽  
Vol 2672 (10) ◽  
pp. 224-235 ◽  
Author(s):  
Yuxiang Yang ◽  
Jie Li ◽  
Chao Wen ◽  
Ping Huang ◽  
Qiyuan Peng ◽  
...  
Keyword(s):  
Travel Behavior ◽  
High Speed ◽  
Operating Costs ◽  
Line Planning ◽  
High Speed Railway ◽  
Planning Stage ◽  
Solution Approach ◽  
Planning Optimization ◽  
Proposed Model

To solve bottlenecks and capacity shortages in railway corridors, it is necessary to consider passengers’ temporal-spatial preferences in conjunction with train dispatching decisions at the line planning stage. A design of the departure and stop plans which is based on the passengers’ preferences would guarantee a high quality of service. This paper presents a line planning optimization model for high-speed railway (HSR) operations that addresses both the operating costs of lines and passengers’ preferences through a bi-level integer programming (IP) problem. Using actual travel data from the Shenzhen–Changsha HSR in China, we investigate passengers’ travel behavior during different time periods and between several origin and destination (OD) pairs to characterize their spatial-temporal preferences. An IP model is then developed that maximizes the degree of passenger departure time satisfaction (DTS) at the higher level and the operating costs of lines at the lower level. Due to the complexity of the problem, a methodology is proposed to find a conflict-free solution for the proposed model to find train frequencies in each block and their stop plans at each station between the upper- and lower-level models. It is shown that a given passenger trip demand between an origin and a destination could become more flexible by analyzing its time characteristics and the DTS. Finally, a case study is presented to show the effectiveness of the model and the solution approach.

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 Modeling and Algorithms of the Crew Rostering Problem with Given Cycle on High-Speed Railway Lines

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Zhiqiang Tian ◽  
Huimin Niu
Keyword(s):  
High Speed ◽  
Ant Colony Algorithm ◽  
Set Covering ◽  
Covering Problem ◽  
High Speed Railway ◽  
Crew Rostering ◽  
Crew Rostering Problem ◽  
Plan Making ◽  
Higher Regularity ◽  
Improved Ant Colony Algorithm

This paper studies the modeling and algorithms of crew roster problem with given cycle on high-speed railway lines. Two feasible compilation strategies for work out the crew rostering plan are discussed, and then an integrated compilation method is proposed in this paper to obtain a plan with relatively higher regularity in execution and lower crew members arranged. The process of plan making is divided into two subproblems which are decomposition of crew legs and adjustment of nonmaximum crew roster scheme. The decomposition subproblem is transformed to finding a Hamilton chain with the best objective function in network which was solved by an improved ant colony algorithm, whereas the adjustment of nonmaximum crew rostering scheme is finally presented as a set covering problem and solved by a two-stage algorithm. The effectiveness of the proposed models and algorithms are testified by a numerical example.

scholarly journals Sustainable Location Selection of Data Centers: Developing a Multi-Criteria Set-Covering Decision-Making Methodology

2020 ◽  
Vol 19 (03) ◽  
pp. 741-773
Author(s):  
Siamak Kheybari ◽  
Mansoor Davoodi Monfared ◽  
Hadis Farazmand ◽  
Jafar Rezaei
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Social Economic ◽  
Set Covering ◽  
Online Questionnaire ◽  
Location Selection ◽  
Sustainability Criteria ◽  
Proposed Model ◽  
Covering Model ◽  
Selection Of

In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of specialists in Iran was asked to take part in an online questionnaire, based on best–worst method (BWM), to determine the weight of the criteria included in the proposed framework, after which a number of potential locations are evaluated on the basis of the criteria. The proposed model is evaluated under a number of settings. Using the proposed multi-criteria set-covering model, not only the utility of candidate places is evaluated by sustainability criteria but also all service applicants are covered by at least one data center with a specific coverage radius.

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 Optimal Differential Pricing for Intercity High-Speed Railway Services with Time-Dependent Demand and Passenger Choice Behaviors under Capacity Constraints

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Huanyin Su ◽  
Shuting Peng ◽  
Lianbo Deng ◽  
Weixiang Xu ◽  
Qiongfang Zeng
Keyword(s):  
Optimization Model ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Solution Space ◽  
Capacity Constraints ◽  
Time Dependent ◽  
High Speed Railway ◽  
Distribution Features ◽  
Differential Pricing ◽  
Dependent Demand

Differential pricing of trains with different departure times caters to the taste heterogeneity of the time-dependent (departure time) demand and then improves the ticket revenue of railway enterprises. This paper studies optimal differential pricing for intercity high-speed railway services. The distribution features of the passenger demand regarding departure times are analyzed, and the time-dependent demand is formulated; a passenger assignment method considering departure periods and capacity constraints is constructed to evaluate the prices by simulating the ticket-booking process. Based on these, an optimization model is constructed with the aim of maximizing the ticket revenue and the decision variables for pricing train legs. A modified direct search simulated annealing algorithm is designed to solve the optimization model, and three random generation methods of new solutions are developed to search the solution space efficiently. Experimental analysis containing dozens of trains is performed on Wuhan-Shenzhen high-speed railway in China, and price solutions with different elastic demand coefficients ( ϕ ) are compared. The following results are found: (i) the optimization algorithm converges stably and efficiently and (ii) differentiation is shown in the price solutions, and the optimized ticket revenue is influenced greatly by ϕ , increasing by 7%–21%.

scholarly journals Track allocation optimization in high-speed railway stations from infrastructure management and service perspectives

2018 ◽  
Vol 51 (7-8) ◽  
pp. 243-259 ◽  
Author(s):  
Qin Zhang ◽  
Xiaoning Zhu ◽  
Li Wang
Keyword(s):  
Simulated Annealing ◽  
High Speed ◽  
Simulated Annealing Algorithm ◽  
Accurate Method ◽  
Nonlinear Integer Programming ◽  
Walking Distance ◽  
Infrastructure Management ◽  
High Speed Railway ◽  
Railway Stations ◽  
Annealing Algorithm

Background: The high-speed railway has been developed rapidly, making track allocation optimization in high-speed railway stations one of the most important problems for traffic control. Methods: This paper proposes a 0-1 nonlinear integer programming model from both infrastructure management and service perspectives to solve this problem at the tactical level. The goal is to balance the track occupation time and at the same time to minimize the total walking distance between the entrance hall and the platforms for all passengers. A pre-calculation technique of time points considering the preparation of the route and a line group method are firstly studied. In order to solve the programming, the simulated annealing algorithm is applied. Results: A case of a China high-speed railway station is used to verify the effectiveness of this model. The optimized result is much better than the original plan in some key indicators. A comparison between the proposed algorithm and an accurate method, the branch-and-bound, is demonstrated. The simulated annealing algorithm obtains almost the same result as the accurate method in a much shorter time. Conclusions: The proposed model is practicable for the the high-speed railway stations.

Sign in / Sign up

Export Citation Format

Share Document