Research on Optimization Algorithm of Single-block Train Formation Plan of Technical Station
DOI:
https://doi.org/10.15837/ijccc.2023.5.5255Abstract
The optimization of train formation plan is a large-scale combinatorial optimization problem, which is difficult to solve. This paper mainly studies the optimization algorithm of the single-block train formation plan. The corresponding mathematical model is established by consulting relevant literature, and a positive feedback search algorithm based on absolute conditions is proposed. First of all, the wagon flow that meets the absolute conditions directly runs through train flow without making other choices. For the wagon flow that does not meet the absolute conditions, select the target station to reach directly according to the probability. The probability of wagon flow selecting a station is calculated according to the pheromone of the wagon flow at the station. At the same time, a pheromone update strategy with positive feedback mechanism is proposed to make the search process converge. Finally, the feasibility of the algorithm and the necessity of introducing absolute conditions into the algorithm are verified by taking eight technical stations in the linear direction of the road network as examples.References
Yuan, Z.; Yuan, X.; Yang, Y et al. (2023). Greenhouse gas emission analysis and measurement for urban rail transit: a review of research progress and prospects, Digital Transportation and Safety, 1(1), 37-52, 2023.
https://doi.org/10.48130/DTS-2023-0004
Yaghini, M.; Momeni, M.; Sarmadi, M. (2015). A hybrid solution method for fuzzy train formation planning, Applied Soft Computing, 31, 257-265, 2015.
https://doi.org/10.1016/j.asoc.2015.02.039
Lin, B.; Tian, Y.; Wang, Z. (2011). The Bi-level Programming Model for Optimizing Train Formation Plan and Technical Station Load Distribution Based on the Remote Re-classification Rule, China Railway Science, 32(5), 108-113, 2011.
Xiao, J.; Lin, B.; Wang, J. (2018). Solving the Train Formation Plan Network Problem of the Single-block Train and Two-block Train Using a Hybrid Algorithm of Genetic Algorithm and Tabu Search, Transportation Research Part C: Emerging Technologies, 86, 124-146, 2018.
https://doi.org/10.1016/j.trc.2017.10.006
Xu, H.; Ma, J. J.; Long, Z.; Long, J. C.; Yang, H. (2006). Study on the Model and Algorithm of the Formation Plan of Single Group Trains at Technical Service Stations, Journal of the China Railway Society, (03), 12-17, 2006.
Badetskii, A.; Medved, O. (2021). Improving the Stability of the Train Formation Plan to Uneven Operational Work, Transportation Research Procedia, 54, 559-567, 2021.
https://doi.org/10.1016/j.trpro.2021.02.108
Papakhov, O. Y.; Lohvinov, O. M. (2006). Elements of Improving the Methods of Calculations of Train Formation Plan, Science and Transport Progress, (12), 91-92, 2006.
https://doi.org/10.15802/stp2006/18591
Lin, B.; Zhao, Y.; Lin, R.; Liu, C. (2021). Integrating Traffic Routing Optimization and Train Formation Plan Using Simulated Annealing Algorithm, Applied Mathematical Modelling, 93, 811- 830, 2021.
https://doi.org/10.1016/j.apm.2020.12.031
Wang, W.; Liu, J.; Xi, J. (2009). A Multi-agent Model for Optimizing Train Formation Plan, Information and Computing Science, 2009. ICIC '09. Second International Conference on, 2009.
https://doi.org/10.1109/ICIC.2009.375
Yang, Y.; Tian, N.; Wang, Y.; Yuan, Z. (2022). A Parallel Fp-growth Mining Algorithm with Load Balancing Constraints for Traffic Crash Data, International Journal of Computers Communications and Control, 17(4), 2022.
https://doi.org/10.15837/ijccc.2022.4.4806
Yang, Y.; Yang, B.; Yuan, Z et al. (2023). Modeling and Comparing Two Modes of Sharing Parking Spots at Residential Area: Real-time and Fixed-time Allocation, IET Intelligent Transport Systems, 2023.
https://doi.org/10.1049/itr2.12343
Butko, T.; Prokhorov, V.; Chekhunov, D. (2017). Devising a Method for the Automated Calculation of Train Formation Plan by Employing Genetic Algorithms, Eastern-European Journal of Enterprise Technologies, 1(3 (85)), 55-61, 2017.
https://doi.org/10.15587/1729-4061.2017.93276
Lin, B.; Wang, Z.; Zhao, Y. (2021). A Train Formation Plan with Elastic Capacity for Large-Scale Rail Networks, arXiv preprint arXiv:2111.03473, 2021.
Xiao, W.; Yue, Y.; Chen, F. (2019). Research on Train Formation Plan Optimization in Railway Network Based on Branch-and-Price Algorithm., In 2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC), pp. 1-4, 2019.
https://doi.org/10.1109/BESC48373.2019.8963192
Negrey, V. Y.; Shkuryn, K. M. (2018). Synergetic Approach to the Calculation of One-group TrainFormation Plan, Science and Transport Progress Bulletin of Dnipropetrovsk National University of Railway Transport, 63, 2018.
Zhang, X.; Kang, L.; Liu, W.; Yao, Y. (2016). Solving Train Formation Plan Problem in Freight Transportation Corridors, In 2016 International Conference on Engineering Science and Management, pp. 102-104, 2016.
https://doi.org/10.2991/esm-16.2016.24
Borojević, S.; Matić, D.; Dragić, M. (2022). An Integrated Intelligent CAD/CAPP Platform: Part II - Operation Sequencing Based on Genetic Algorithm, Tehnički vjesnik, 29(5), 1686-1695, 2022.
https://doi.org/10.17559/TV-20211012084632
Boudjemline, A.; Chaudhry, I.A.; Rafique, A.F.; Elbadawi, I.A.; Aichouni, M.; Boujelbene, M. (2022). Multi-Objective Flexible Job Shop Scheduling Using Genetic Algorithms, Tehnički vjesnik, 29(5), 1706-1713, 2022.
https://doi.org/10.17559/TV-20211022164333
Huang, Y.; Huang, S.; Jin, C. (2021). 3D-Container Loading Problem with a Distribution Plan Based on Hybrid Quantum Genetic Algorithm, Economic Computation And Economic Cybernetics Studies And Research, 55(4), 117-132, 2021.
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