Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search
This paper focuses on discrete dynamic optimization on train rescheduling on single-track railway with the consideration of train punctuality and station satisfaction degree. A discrete dynamic system is firstly described to mimic train rescheduling, and a state transition function is specially desi...
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2020-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2020/8892372 |
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doaj-3976420104de428dbba295b6fd2ed35b2020-12-07T09:08:22ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/88923728892372Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic SearchZhengkun Zhang0Changfeng Zhu1Wenhu Ma2School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, ChinaSchool of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, ChinaSchool of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, ChinaThis paper focuses on discrete dynamic optimization on train rescheduling on single-track railway with the consideration of train punctuality and station satisfaction degree. A discrete dynamic system is firstly described to mimic train rescheduling, and a state transition function is specially designed according to the train departure event. The purpose of this function is to improve simulation efficiency by directly confirming the next discrete time. After the construction and analysis of optimization models to discrete dynamic system, a two-stage heuristic search strategy is developed, by using clustering hierarchy theory and stochastic search strategy, to obtain train departure time and arrival time before each state transition of the system. Finally, a numerical experiment is conducted to verify the proposed system, models, and the heuristic search strategy. The result shows that the discrete dynamic system, together with the state transition function and heuristic search strategy, shows better performance in simulation efficiency and solution quality.http://dx.doi.org/10.1155/2020/8892372 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhengkun Zhang Changfeng Zhu Wenhu Ma |
spellingShingle |
Zhengkun Zhang Changfeng Zhu Wenhu Ma Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search Journal of Advanced Transportation |
author_facet |
Zhengkun Zhang Changfeng Zhu Wenhu Ma |
author_sort |
Zhengkun Zhang |
title |
Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search |
title_short |
Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search |
title_full |
Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search |
title_fullStr |
Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search |
title_full_unstemmed |
Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search |
title_sort |
discrete optimization on train rescheduling on single-track railway: clustering hierarchy and heuristic search |
publisher |
Hindawi-Wiley |
series |
Journal of Advanced Transportation |
issn |
0197-6729 2042-3195 |
publishDate |
2020-01-01 |
description |
This paper focuses on discrete dynamic optimization on train rescheduling on single-track railway with the consideration of train punctuality and station satisfaction degree. A discrete dynamic system is firstly described to mimic train rescheduling, and a state transition function is specially designed according to the train departure event. The purpose of this function is to improve simulation efficiency by directly confirming the next discrete time. After the construction and analysis of optimization models to discrete dynamic system, a two-stage heuristic search strategy is developed, by using clustering hierarchy theory and stochastic search strategy, to obtain train departure time and arrival time before each state transition of the system. Finally, a numerical experiment is conducted to verify the proposed system, models, and the heuristic search strategy. The result shows that the discrete dynamic system, together with the state transition function and heuristic search strategy, shows better performance in simulation efficiency and solution quality. |
url |
http://dx.doi.org/10.1155/2020/8892372 |
work_keys_str_mv |
AT zhengkunzhang discreteoptimizationontrainreschedulingonsingletrackrailwayclusteringhierarchyandheuristicsearch AT changfengzhu discreteoptimizationontrainreschedulingonsingletrackrailwayclusteringhierarchyandheuristicsearch AT wenhuma discreteoptimizationontrainreschedulingonsingletrackrailwayclusteringhierarchyandheuristicsearch |
_version_ |
1715013476697505792 |