Solution of the Problem of Empty Car Distribution between Stations and Planning of Way-Freight Train Route Using Genetic Algorithms

  • Authors

    • Viktor Prokhorov
    • Tetiana Kalashnikova
    • Liliia Rybalchenko
    • Yuliia Riabushka
    • Denys Chekhunov
    2018-09-15
    https://doi.org/10.14419/ijet.v7i4.3.19803
  • empty car distribution, genetic algorithms, integer combinatorial optimization problem, railway polygon, way-freight train route.

  • Abstract

    In this paper we consider the problem of distributing empty freight cars in a railway polygon. We show how the process can be improved using an optimization model. The optimization model can be characterized as a combination of minimum-cost flow problem with vehicle routing problem. In general, problem of empty railroad car distribution between stations and definition of way-freight train route is presented as integer combinatorial optimization problem. Computational tests show that the model can be solved in acceptable time for real size problems, and indicate that the model generates distribution plans that can improve the quality of the planning process.

     

  • References

    1. [1] Rakhmangulov A.N. (2014), Mathematical model of optimal empty rail car distribution at railway transport nodes (in Russian). Railway Research Institute Bulletin 6, 8–11.

      [2] Dejax, Crainic T. (1987), A review of empty flows and fleet management models in freight transportation. Transportation Science, 21(4), 227–248. http://dx.doi.org/10.1287/trsc.21.4.

      [3] Heydari R., Melachrinoudis E. (2017). A path-based capacitated network flow model for empty railcar distribution. Annals of Operations Research 253 (2), 773.

      [4] Narisetty A.K., Richard J.P., Ramcharan D., Murphy D., Minks G., Fuller J. (2008), An optimization model for empty freight car assignment at Union Pacific Railroad. Interfaces 38 (2), 89–102.

      [5] Xiong H., Lu W., Wen H. (2002), Genetic algorithm used in railway empty car allocating problem. China Railway Science 23(4), 118–121.

      [6] Zhang X., Zhang Q. (2003), Study on the optimization method of empty car distribution based on knowledge constraints. Journal of the China Railway Society 25(6), 14–20.

      [7] Wang H., Yan, Tan Y. (2008), Network node of railway refrigerator empty car adjustment in ant colony algorithm. China Railway Science 29(2), 131–135.

      [8] Lei Z., He S., Song R., Cai J. (2005), Stochastic chance-constrained model and genetic algorithm for empty car distribution in railway transportation. Journal of the China Railway Society 27(5), 1–5.

      [9] Joborn M., Crainic T.G., Gendreau M., Holmberg K., Lundgren J.T. (2004), Economies of scale in empty freight car distribution in scheduled railways Transportation Science 38(2), 121–134.

      [10] Fukasawa R., Poggi de Aragão M.V., Porto O., Uchoa E. (2002), Solving the freight car flow problem to optimality. Electronic Notes in Theoretical Computer Science 66(6), 42–52.

      [11] Sifaleras A. (2013), Minimum cost network flows: Problems, algorithms, and software. Yugoslav journal of operations research 23(1), 3–17. DOI: 10.2298/YJOR121120001S

      [12] Laporte G, Toth P, Vigo D (2013), Vehicle routing: historical perspective and recent contributions. EURO Journal on Transportation and Logistics 2(1-2), 1–4.

      [13] Chabrier A. (2006), Vehicle routing problem with elementary shortest path based column generation. Computers and Operations Research 33(10), 2972–2990.

      [14] Baldacci R., Mingozzi A., Roberti R. (2012), Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. European Journal of Operational Research 218(1), 1–6.

      [15] Meng Z.Q., Dang C.Y., Jiang M., Shen R. (2011), A smoothing objective penalty function algorithm for inequality constrained optimization problems. Numer. Funct. Anal. Optimiz. 32, 806–820.

      [16] Yu C., Teo K.L., Zhang L., Bai Y. (2010), A new exact penalty function method for continuous inequality constrained optimization problems. Journal of industrial and management optimization 6(4), 895–910. doi:10.3934/jimo.2010.6.895

      [17] Ince I., Sezen B., Saridogan E, Ince H. (2009), An evolutionary computing approach for the target motion analysis (TMA) problem for underwater tracks. Expert Systems with Applications 36(2), 3866–3879.

      [18] Ryoo J., Hajela P. (2004), Handling variable string lengths in ga based structural topology optimization. Struct Multidisc Optim 26, 318–325.

      [19] Jakiela M.J., Chapman C., Duda J., Adewuya A., Saitou K. (2000), Continuum structural topology design with genetic algorithms. Comput Methods Appl Mech Eng 186, 339–356.

      [20] Goldberg D.E., Korb B. Deb K. (1989). Messy genetic algorithms: motivation, analysis, and first results. Complex Systems 3(5), 493–530.

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  • How to Cite

    Prokhorov, V., Kalashnikova, T., Rybalchenko, L., Riabushka, Y., & Chekhunov, D. (2018). Solution of the Problem of Empty Car Distribution between Stations and Planning of Way-Freight Train Route Using Genetic Algorithms. International Journal of Engineering & Technology, 7(4.3), 275-278. https://doi.org/10.14419/ijet.v7i4.3.19803

    Received date: 2018-09-18

    Accepted date: 2018-09-18

    Published date: 2018-09-15