A new method for solving the problem on the organization of wagon flows under condition of energy efficiency of transportation

Authors

  • Oleksandr Papakhov Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0003-2357-8158
  • Natalya Logvinova Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0002-9350-881X
  • Olesya Kharchenko Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0003-2068-0640
  • Andriy Milyanych Lviv Branch of Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan I. Blazhkevych str., 12а, Lviv, Ukraine, 79052, Ukraine https://orcid.org/0000-0003-3583-792X
  • Victor Sichenko Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010, Ukraine https://orcid.org/0000-0002-9533-2897

DOI:

https://doi.org/10.15587/1729-4061.2017.111940

Keywords:

knapsack problem, set function, vector optimization, organization of wagon flows, energy efficiency of transportation

Abstract

The paper considers solving a problem of rational organization of wagon flows in a polygon of selected technological railroad stations using a technique for solving a knapsack problem employing set functions. Based on the results of present work, the authors developed a method for solving a knapsack-type problem that makes it possible to adapt the algorithm of solving a vector optimization problem to the rational system of organizing wagon flows in trains without using differentiation operations and to solve a basic optimization problem employing the Lagrange multipliers. The applicability of the Lagrange method was proved for the problems on a conditional extremum in terms of set functions. Its special feature is the rejection of Boolean variables. We confirmed correctness of the mathematical notation of solution to a knapsack-type problem and proved adequacy of the proposed algorithm, as well as adapted it for adjusting a plan of freight trains formation in order to improve energy efficiency of transportation. By reducing the complexity of the problem, it has become possible to reduce computer processor time needed for calculation, and employ this algorithm when designing an automated work place (AWP) for an engineer responsible for planning the formation of trains. It should be specially noted that a reduction of the time needed to solve a problem makes it possible to timely adjust the plan of freight trains formation, to eliminate a lot of irrational variants when handling wagons at technical stations.

The proposed algorithm helps identify variants to direct train flows to the most promising destinations at minimal energy cost for transportation. Limitations of the proposed approach include a closed cycle of routes of the loaded wagons and part of these routes traveled unloaded until the next loading. In some cases, there is a need to change a weight of the train composition, associated with fractures of weight, and, therefore, a change in the balance between wagon flows and train flows. 

Author Biographies

Oleksandr Papakhov, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

PhD, Associate Professor

Department of operational management

Natalya Logvinova, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

PhD, Associate Professor

Department of operational management

Olesya Kharchenko, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

PhD, Associate Professor

Department of operational management

Andriy Milyanych, Lviv Branch of Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan I. Blazhkevych str., 12а, Lviv, Ukraine, 79052

PhD

Department of operational management

Victor Sichenko, Dnipropetrovsk National University of Railway Transport named after academician V. Lazaryan Lazaryana str., 2, Dnipro, Ukraine, 49010

Doctor of Technical Sciences, Professor

Department of Intellectual power supply systems

References

  1. Mazurenko, O. O., Kudryashov, A. V. (2014). Efficiency of formation of two-group trains in operative conditions of organization of carriages. Collection of scientific works of the State Research and Production Enterprise «Transport systems and technologies of transportation», 7, 50–55.
  2. González, E. M., Sánchez, G. G., Romero, J. M. M. (2014). Analysis and Viability of Railway Exportation to Europe from the South of Spain. Procedia – Social and Behavioral Sciences, 160, 264–273. doi: 10.1016/j.sbspro.2014.12.138
  3. Baushev, A. N., Osminin, A. T., Osminin, L. A. (2013). Mathematical model of multiphase railroad cargo transportation. Mathematical modeling, 25 (10), 108–122.
  4. Papakhov, A. Yu. (2016). Use of the set-function method for the rational organization of car-stream flows. Transport systems and transport technologies, 12, 69–74.
  5. Reznikov, A. E., Fedorin, A. N. (2009). Mathematical Models and Algorithms for Solving the Problems of Optimal Loading of Vehicles. In Sat. tr. 11th International Scientific and Industrial Forum "Great Rivers". ICEF. Problems and prospects of development of educational, scientific and innovative transport complexes. Nizhniy Novgorod.
  6. Мyamlin, S. V., Zhyzhko, K. V. (2014). Upgrading of economic simulation methods for increasing efficiency of investments. Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, 6 (54), 34–41. doi: 10.15802/stp2014/32656
  7. Klamroth, K., Wiecek, M. M. (2015). Dynamic Programming Approaches to the Multiple Criteria Knapsack Problem. Clemson University Clemson, SC USA, 30.
  8. Bazgan, C., Hugot, H., Vanderpooten, D. (2007). An Efficient Implementation for the 0-1 Multi-objective Knapsack Problem. Vol. 4525. Lecture Notes in Computer Science. Springer, 406–419. doi: 10.1007/978-3-540-72845-0_31
  9. Beausoleil, R. P., Baldoquin, G., Montejo, R. A. (2007). Multi-start and path relinking methods to deal with multiobjective knapsack problems. Annals of Operations Research, 157 (1), 105–133. doi: 10.1007/s10479-007-0199-8
  10. Lin, B. (2017). Integrating car path optimization with train formation plan: a non-linear binary programming model and simulated annealing based heuristics. arXiv. Available at: https://arxiv.org/ftp/arxiv/papers/1707/1707.08326.pdf
  11. Bosov, A. A. (2007). Functions of sets and their application. Dneprodzerzhinsk: Izd. House "Andrew", 182.
  12. Lazorev, A. A., Gafarov, E. R. (2011). Theory of schedules. Tasks and algorithms. Мoscow: Publishing House of Moscow State University. M. V. Lomonosov, 222.

Downloads

Published

2017-10-30

How to Cite

Papakhov, O., Logvinova, N., Kharchenko, O., Milyanych, A., & Sichenko, V. (2017). A new method for solving the problem on the organization of wagon flows under condition of energy efficiency of transportation. Eastern-European Journal of Enterprise Technologies, 5(4 (89), 57–62. https://doi.org/10.15587/1729-4061.2017.111940

Issue

Section

Mathematics and Cybernetics - applied aspects