TY - JOUR
T1 - Railway capacity allocation modeling using a genetic algorithm
AU - Kim, Hyunseung
AU - Jeong, In Jae
AU - Park, Dongjoo
N1 - Publisher Copyright:
© 2017, SAGE Publications Ltd. All rights reserved.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85054806456&partnerID=8YFLogxK
U2 - 10.3141/2608-13
DO - 10.3141/2608-13
M3 - Article
AN - SCOPUS:85054806456
SN - 0361-1981
VL - 2608
SP - 115
EP - 124
JO - Transportation Research Record
JF - Transportation Research Record
IS - 1
ER -