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Determination of Truck Maintenance Allocation Scheme Based on SA-GA

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
As an important department of railway transportation and production, large freight train depot is responsible for the regular overhaul and maintenance of railway trucks. The shunting operation of freight train depot covers the whole process of railway trucks entering, storing, overhauling and leaving the depot. It is an important step in the implementation of the maintenance operation. Usually, shunting personnel in the depot transport the trucks to be overhauled to the maintenance line by relying on the shunting operation plan, which is the key to determine the shunting operation plan according to the distribution relationship between vehicles and maintenance. Firstly, this paper analyzes the process of centralized shunting operation in the freight train depot and the factors affecting the time-consuming based on the research idea of flexible workshop scheduling problem. Then, on the premise that the proportion of the weight coefficient will have an impact on the time-consuming of truck busy and shunting in the shunting process, and with the goal of minimizing the time-consuming of truck maintenance busy and shunting, the allocation model between trucks and maintenance lines is established; In addition, an improved genetic algorithm is proposed to solve the established model; Finally, combined with the maintenance of railway trucks in a large freight train depot, an example analysis is carried out on this basis. The results demonstrate that using simulated annealing genetic algorithm to solve the model can obtain the allocation scheme between railway trucks and maintenance operation line. Under the influence of three different coefficients, compared with genetic algorithm, simulated annealing genetic algorithm can reduce the detention time of railway trucks in depot by 0.21%, 0.09% and 0.12% respectively, which is beneficial to reducing the detention time of maintenance vehicles in depot, It plays a positive role in improving the maintenance efficiency of trucks in the depot, and also provides new ideas for the research of railway truck shunting
Rocznik
Strony
59--71
Opis fizyczny
Bibliogr. 20 poz., rys., tab., wykr.
Twórcy
autor
  • School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou China
autor
  • School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou China
autor
  • School of Automation Electrical Engineering, Lanzhou Jiaotong University, Lanzhou China
autor
  • School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou China
autor
  • School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou China
Bibliografia
  • [1] Tong, J. N., Nie, L., He, Z. H. (2016) Optimization of first level maintenance operation plan of EMU Operation Station Based on genetic algorithm. Railway Transport and Economy, 38(08): 59-65.
  • [2] Ma, L., Zhang, X. X., Guo, J. (2016). Research on track utilization of railway marshalling yard shunting yard based on heuristic backtracking algorithm. Journal of the China Railway Society, 38(08), 16-22.
  • [3] Per, Munk. Jacobsen., David, Pisinger. (2011) Train shunting at a workshop area. Flexible Services and Manufacturing Journal, 23(02) 156-180.
  • [4] Brady, Gilg., Torsten, Klug., Joseph, Paat., et al. (2018) Conflict-free railway track assignment at depots. Journal of Rail Transport Planning & Management, 08(01) 16-28.
  • [5] Wang, Z. K., Shi, T. Y., Zhang, W. J, & Wang, H. (2013) Optimization model and algorithm of shunting operation plan in EMU Operation Station. Journal of the China Railway Society, 35(08), 1-9.
  • [6] Zhang, W. J., Shi, T. Y., Chen, Y.(2013) Optimization model and algorithm of train line operation scheme in EMU Operation. China Railway Science, 34(01), 121-125.
  • [7] Guo, X. L., Song, R., Li, H. D. (2016) Preparation and optimization of shunting operation plan in EMU Operation Station. China Railway Science, 37(01), 117-123.
  • [8] Hu, Z. A., Zheng, L., Zhou, S. (2022) Optimization of shunting operation plan of EMU station considering reasonable occupation of train positions. Journal of Southwest Jiaotong University, 57(01), 65-73.
  • [9] Shi, J T., Li, H. D., Cao, H. et al.(2022) Preparation of shunting operation plan of EMU station considering flexible storage and occupation of train positions. China Railway Science, 43(01) 152-162.
  • [10] Lei, D. Y., Guo, C., Zhang, Y. (2016) Reasonable scheduling for arrival-departure track operations in railway stations. Transportation Planning & Technology, 39(06), 1-16.
  • [11] Zheng, K. D., Cha, W. X., Wang, M. et al. (2020) Route selection optimization of enterprise hub stations based on time continuity. Journal of the China Railway Society, 42(10): 1-8.
  • [12] Zhao, J., Zhang, S. Y., Peng, Q. Y. (2020). Application Optimization of Shunting Line in Railway Technical Station Considering Shunting Cost. Journal of the China Railway Society, 42(08), 10-22.
  • [13] Lv, X. X., Ni, S. Q., Cheng, D. J. (2015) Research on optimization model of shunting operation in positioning operation passenger station. Journal of the China Railway Society, 37(12), 1-7.
  • [14] Wang, J. X., Lin, B. L., Wang, Z. K., & Li, J. (2016) Optimization model and solution algorithm of shunting operation plan in EMU station. Transportation System Engineering and Information, 16(06), 122-127+141.
  • [15] Zhang, B. J., Pen, Q.Y., Li, L. et al. (2020) Shunting operation planning method of pick-up and coupling train for optimizing the number of shunting vehicles. Journal of the China Railway Society, 42(03) 11-20.
  • [16] Shi, J. T., Li, H. D., Giulio, E. Cantarella. (2019) Optimization of the shunting operation plan at electric multiple units depots[J]. Journal of Advanced Transportation, 12(06), 1-16.
  • [17] Wang, Y. L., Xiao, Y., Lei, Y. C., et al. (2012) Automatic preparation method of marshalling hook plan of uncoupling train based on sorted binary tree. China Railway Science, 33(03), 116-122.
  • [18] Konrad, Lewczuk. (2015) The concept of genetic programming in organizing internal transport processes. Archives of Transport, 34(02), 61-74.
  • [19] Ma, Y. J., Yun, W. X. (2012) Research progress of genetic algorithm. Journal of computer application research, 29(04), 1201-1210.
  • [20] Zheng, X. H., Bao, J. S., Ma, Q. W., & Zhang, L. S. (2022) Spinning workshop scheduling system based on simulated annealing genetic algorithm. Journal of Textile Research, 41(06), 36-41.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bd1483c3-a2cc-43fe-8ec9-ed261f7a3aba
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