Simulation Model to Optimize Turnover Schedule for Train Locomotives
This work relates to a suggested simulation model to optimize turnover schedule for train locomotives operating in train flow service. It is first time the problem was formulated as a strict optimization model - a dynamic transportation problem. On the functional level, the main goal was to minimize...
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| Format: | Article |
| Language: | Russian |
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Joint Stock Company «Railway Scientific and Research Institute»
2015-04-01
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| Series: | Вестник Научно-исследовательского института железнодорожного транспорта |
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| Online Access: | https://www.journal-vniizht.ru/jour/article/view/23 |
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| author | P. A. Kozlov S. P. Vakulenko |
| author_facet | P. A. Kozlov S. P. Vakulenko |
| author_sort | P. A. Kozlov |
| collection | DOAJ |
| description | This work relates to a suggested simulation model to optimize turnover schedule for train locomotives operating in train flow service. It is first time the problem was formulated as a strict optimization model - a dynamic transportation problem. On the functional level, the main goal was to minimize overall costs which are directly related to locomotives operation and to losses due to train delays. At present the problem has been solved through various heuristic procedures, which fail to find the optimum alternative due to a huge amount of multivariate solutions. The dynamic traffic problem was taken as a starting point for simulation model development. In the process of calculations the dynamic problem is reduced to the static one by use of time multiplication method. The model helps to calculate routes for each locomotive with due account for train flow pattern, location of trains at the start of calculations, and specified traffic schedule. The lowest total costs of locomotives use and losses for train delays can be taken as a criterion of optimality. The output reflects the complete nature of productive locomotive operations, train operation dynamics and resultant delays. Additionally, each locomotive’s operation mode and each train’s timetable can be seen. For calculation tests there was selected an existing main line section between stations Druzhinino and Vekovka including 9 stations; traffic data were chosen close to reality. Actually, the above sub-division employs 180 locomotives. Various experiments were held. The minimum number of locomotives necessary to secure faultless operation (195 units) was calculated. The model generates different results, which characterize train operations. Output includes a schedule for each locomotive, timetable for each train, average operating results for locomotives, and train delays data. For a selected criterion the model suggests calculations of an optimal number of locomotives and their best locations at the start of calculations. In order to register depot orders to locomotives, a multistage procedure for solving dynamic transportation problems was proposed. In order to check the feasibility of generated results, another imitational model was built which may reconsider many of non-definable factors. Operating principles for a two-level model were reviewed by the authors in their earlier publications. The model can be used as an optimizing unit in the Locomotive Computer-Assisted Management System - in sphere of day-to-day management and for calculating the optimum turnover modes. Automated management of locomotive fleet operations throughout the railway network will deliver significant technological and economical effects. |
| format | Article |
| id | doaj-art-b52b35def04e4d208ad31bd3a7058d6e |
| institution | Kabale University |
| issn | 2223-9731 2713-2560 |
| language | Russian |
| publishDate | 2015-04-01 |
| publisher | Joint Stock Company «Railway Scientific and Research Institute» |
| record_format | Article |
| series | Вестник Научно-исследовательского института железнодорожного транспорта |
| spelling | doaj-art-b52b35def04e4d208ad31bd3a7058d6e2025-08-20T03:37:38ZrusJoint Stock Company «Railway Scientific and Research Institute»Вестник Научно-исследовательского института железнодорожного транспорта2223-97312713-25602015-04-0102152010.21780/2223-9731-2015-0-2-15-2023Simulation Model to Optimize Turnover Schedule for Train LocomotivesP. A. Kozlov0S. P. Vakulenko1Research & Production Holding STRATEGInstitute for Management and Information Technologies at Moscow State University of Railway Engineering (MIIT)This work relates to a suggested simulation model to optimize turnover schedule for train locomotives operating in train flow service. It is first time the problem was formulated as a strict optimization model - a dynamic transportation problem. On the functional level, the main goal was to minimize overall costs which are directly related to locomotives operation and to losses due to train delays. At present the problem has been solved through various heuristic procedures, which fail to find the optimum alternative due to a huge amount of multivariate solutions. The dynamic traffic problem was taken as a starting point for simulation model development. In the process of calculations the dynamic problem is reduced to the static one by use of time multiplication method. The model helps to calculate routes for each locomotive with due account for train flow pattern, location of trains at the start of calculations, and specified traffic schedule. The lowest total costs of locomotives use and losses for train delays can be taken as a criterion of optimality. The output reflects the complete nature of productive locomotive operations, train operation dynamics and resultant delays. Additionally, each locomotive’s operation mode and each train’s timetable can be seen. For calculation tests there was selected an existing main line section between stations Druzhinino and Vekovka including 9 stations; traffic data were chosen close to reality. Actually, the above sub-division employs 180 locomotives. Various experiments were held. The minimum number of locomotives necessary to secure faultless operation (195 units) was calculated. The model generates different results, which characterize train operations. Output includes a schedule for each locomotive, timetable for each train, average operating results for locomotives, and train delays data. For a selected criterion the model suggests calculations of an optimal number of locomotives and their best locations at the start of calculations. In order to register depot orders to locomotives, a multistage procedure for solving dynamic transportation problems was proposed. In order to check the feasibility of generated results, another imitational model was built which may reconsider many of non-definable factors. Operating principles for a two-level model were reviewed by the authors in their earlier publications. The model can be used as an optimizing unit in the Locomotive Computer-Assisted Management System - in sphere of day-to-day management and for calculating the optimum turnover modes. Automated management of locomotive fleet operations throughout the railway network will deliver significant technological and economical effects.https://www.journal-vniizht.ru/jour/article/view/23model locomotivetraffic flow of trainsoptimizationoperation mode |
| spellingShingle | P. A. Kozlov S. P. Vakulenko Simulation Model to Optimize Turnover Schedule for Train Locomotives Вестник Научно-исследовательского института железнодорожного транспорта model locomotive traffic flow of trains optimization operation mode |
| title | Simulation Model to Optimize Turnover Schedule for Train Locomotives |
| title_full | Simulation Model to Optimize Turnover Schedule for Train Locomotives |
| title_fullStr | Simulation Model to Optimize Turnover Schedule for Train Locomotives |
| title_full_unstemmed | Simulation Model to Optimize Turnover Schedule for Train Locomotives |
| title_short | Simulation Model to Optimize Turnover Schedule for Train Locomotives |
| title_sort | simulation model to optimize turnover schedule for train locomotives |
| topic | model locomotive traffic flow of trains optimization operation mode |
| url | https://www.journal-vniizht.ru/jour/article/view/23 |
| work_keys_str_mv | AT pakozlov simulationmodeltooptimizeturnoverschedulefortrainlocomotives AT spvakulenko simulationmodeltooptimizeturnoverschedulefortrainlocomotives |