Locomotive Schedule Optimization for Da-qin Heavy Haul Railway
The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model...
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Series: | Mathematical Problems in Engineering |
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doaj-0329975bcc7549b59225259b6b08688d2020-11-24T21:17:04ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/607376607376Locomotive Schedule Optimization for Da-qin Heavy Haul RailwayRuiye Su0Leishan Zhou1Jinjin Tang2School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaThe main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP) hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP) can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid.http://dx.doi.org/10.1155/2015/607376 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ruiye Su Leishan Zhou Jinjin Tang |
spellingShingle |
Ruiye Su Leishan Zhou Jinjin Tang Locomotive Schedule Optimization for Da-qin Heavy Haul Railway Mathematical Problems in Engineering |
author_facet |
Ruiye Su Leishan Zhou Jinjin Tang |
author_sort |
Ruiye Su |
title |
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway |
title_short |
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway |
title_full |
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway |
title_fullStr |
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway |
title_full_unstemmed |
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway |
title_sort |
locomotive schedule optimization for da-qin heavy haul railway |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP) hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP) can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid. |
url |
http://dx.doi.org/10.1155/2015/607376 |
work_keys_str_mv |
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