Communications - Scientific Letters of the University of Zilina 2022, 24(2):D46-D58 | DOI: 10.26552/com.C.2022.2.D46-D58

Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling

Ganna Samchuk ORCID...1, Denis Kopytkov ORCID...1, Alexander Rossolov ORCID...1
O. M. Beketov National University of Urban Economy in Kharkiv, Kharkiv, Ukraine

The article deals with the problem of estimating the rational number and utilization rate of the vehicles' fleet. According to the analysis results of the state-of-the-art literature it has been revealed that the issue of substantiating the rational fleet size and the rate of its utilization were not fully solved. The purpose of the study was to increase the efficiency of servicing transportation orders by determining the required number of vehicles. The goal of the research was the influence of the transportation process parameters on the truck utilization rate. Originating from the probabilistic nature of the transportation process, it has been proposed to use the AnyLogic software product to develop a simulation model for vehicle orders' servicing. From the processing of the experimental results by the regression analysis methods, it has been found that the dependence of changes in the vehicle utilization rate is of a linear form.

Keywords: freight fleet management, utilization rate, experiment, simulation, regression analysis

Received: July 10, 2021; Accepted: October 11, 2021; Prepublished online: December 15, 2021; Published: April 1, 2022  Show citation

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Samchuk, G., Kopytkov, D., & Rossolov, A. (2022). Freight Fleet Management Problem: Evaluation of a Truck Utilization Rate Based on Agent Modeling. Communications - Scientific Letters of the University of Zilina24(2), D46-58. doi: 10.26552/com.C.2022.2.D46-D58
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References

  1. AULIN, V., HRYNKIV A., LYASHUK, O., VOVK, YU., LYSENKO S., HOLUB, D., ZAMOTA, T., PANKOV, A., SOKOL, M., RATYNSKYI, V., LAVRENTIEVA, O. Increasing the functioning efficiency of the working warehouse of the "UVK Ukraine" company transport and logistics center. Communications - Scientific Letters of the University of Zilina [online]. 2020, 22(2), p. 3-14. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2020.2.3-14 Go to original source...
  2. LUKASIK, Z., KUSMINSKA-FIJALKOWSKA, A., OLSZANSKA, S. Improvement of the logistic processes using the reverse logistics concept. Communications - Scientific Letters of the University of Zilina [online]. 2021, 23(3), p. 174-183. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2021.3.A174-A183 Go to original source...
  3. NAUMOV, V., ZHAMANBAYEV, A., AGABEKOVA, D., ZHANBIROV ZH., TARAN, I. Fuzzy-logic approach to estimate the passengers' preference when choosing a bus line within the public transport system. Communications - Scientific Letters of the University of Zilina [online]. 2021, 23(3), p. 150-157. ISSN 1335-4205, eISSN 2585-7878. Available from: https://doi.org/10.26552/com.C.2021.3.A150-A157 Go to original source...
  4. BIELLI, M., BIELLI, A., ROSSI, R. Trends in models and algorithms for fleet management. Procedia Social and Behavioral Sciences [online]. 2011, 20, p. 4-18. ISSN 1877-0428. Available from: https://doi.org/10.1016/j.sbspro.2011.08.004 Go to original source...
  5. HOFF, A., ANDERSSON, H., CHRISTIANSEN, M., HASLE G., LOKKETANGEN, A. Industrial aspects and literature survey: fleet composition and routing. Computers and Operations Research [online]. 2010, 37(12), p. 2041-2061. ISSN 0305-0548. Available from: https://doi.org/10.1016/j.cor.2010.03.015 Go to original source...
  6. BEAUJON, G. J., TURNQUIST, M. A. A model for fleet sizing and vehicle allocation. Transportation Science [online]. 1991, 25(1), p. 19-45. ISSN 0041-1655, eISSN 1526-5447. Available from: https://doi.org/10.1287/trsc.25.1.19 Go to original source...
  7. DU, J. Y., BRUNNER, J. O., KOLISCH, R. Obtaining the optimal fleet mix: a case study about towing tractors at airports. Omega [online]. 2016, 64, p. 102-114. ISSN 0305-0483. Available from: https://doi.org/10.1016/j.omega.2015.11.005 Go to original source...
  8. WU, P., HARTMAN, J. C., WILSON, G. R. An integrated model and solution approach for fleet sizing with heterogeneous assets. Transportation Science [online]. 2005, 39(1), p. 87-103. ISSN 0041-1655, eISSN 1526-5447. Available from: https://doi.org/10.1287/trsc.1030.0050 Go to original source...
  9. LEJDA K., ZIELINSKA, E. Car fleet management problems in enterprise. TEKA. Commission of Motorization and Energetics in Agriculture. 2013, 13(1), p. 89-94. ISSN 1641-7739.
  10. NAUMOV, V. Estimating the vehicles' number for servicing a flow of requests on goods delivery. Transportation Research Procedia [online]. 2017, 27, p. 412-419. ISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2017.12.063 Go to original source...
  11. REDMER, A. Strategic vehicle fleet management - the composition problem. LogForum. 2015, 11(1), p. 119-126. ISSN 1895-2038, eISSN 1734-459X. Available from: http://www.logforum.net/vol 11/issue 1/no 11 Go to original source...
  12. BARRIOS, J. A., GODIER, J. D. Fleet sizing for flexible car sharing systems: simulation-based approach. Transportation Research Record [online]. 2014, 2416(1), p. 1-9. ISSN 0361-1981, eISSN 2169-4052. Available from: https://doi.org/10.3141/2416-01 Go to original source...
  13. ZAK, J., REDMER, A., SAWICKI, P. Multiple objective optimization of the fleet sizing problem for road freight transportation. Journal of Advanced Transportation [online]. 2011, 45(4), p. 379-427. ISSN 0197-6729, eISSN 2042-3195. Available from: https://doi.org/10.1002/atr.111 Go to original source...
  14. XINGYU, L., EPUREANU, B. An agent-based approach to optimizing modular vehicle fleet operation. International Journal of Production Economics [online]. 2020, 228(C), 107733. ISSN 0925-5273. Available from: https://doi.org/10.1016/j.ijpe.2020.107733 Go to original source...
  15. WANG, Y., LIMMER, S., VAN NGUYEN, D., OLHOFER, M., BACK T., EMMERICH, M. Optimizing the maintenance schedule for a vehicle fleet: a simulation-based case study. Engineering Optimization [online]. 2021, ahead-of-print. ISSN 0305-215X, eISSN 1029-0273. Available from: https://doi.org/10.1080/0305215X.2021.1919888 Go to original source...
  16. BISCHOFF, J., MACIEJEWSKI, M. Agent-based simulation of electric taxicab fleets. Transportation Research Procedia [online]. 2014, 4, p. 191-198. ISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2014.11.015 Go to original source...
  17. JIANWEI, R., CHEN, C., GAO, J., FENG, C. An optimization model for fleet sizing and empty pallet allocation considering CO2 emissions. Plos One [online]. 2020, 15(2), e0229544. eISSN 1932-6203. Available from: https://doi.org/10.1371/journal.pone.0229544 Go to original source...
  18. MILENKOVIC, M., BOJOVIC, N. A. fuzzy random model for rail freight car fleet sizing problem. Transportation Research Part C: Emerging Technologies [online]. 2013, 33.p 107-133. ISSN 0968-090X. Available from: https://doi.org/10.1016/j.trc.2013.05.003 Go to original source...
  19. MILENKOVIC, M., BOJOVIC, N., SVADLENKA, L., MELICHAR, V. A stochastic model predictive control to heterogeneous rail freight car fleet sizing problem. Transportation Research Part E: Logistics and Transportation Review [online]. 2015, 82(C), p. 162-198. ISSN 1366-5545. Available from: https://doi.org/10.1016/j.tre.2015.07.009 Go to original source...
  20. SAYARSHAD, H. R., TAVAKKOLI-MOGHADDAM, R. Solving a multi periodic stochastic model of the rail-car fleet sizing by two-stage formulation. Applied Mathematical Modelling [online]. 2010, 34(5), p. 1164-1174. ISSN 0307-904X. Available from: https://doi.org/10.1016/j.apm.2009.08.004 Go to original source...
  21. YAGHINI, M., KHANDAGHABADI, Z. A hybrid metaheuristic algorithm for dynamic rail car fleet sizing problem. Applied Mathematical Modelling [online]. 2013, 37(6), p. 4127-4138. ISSN 0307-904X. Available from: https://doi.org/10.1016/j.apm.2012.09.013 Go to original source...
  22. SAYARSHAD, H. R., GHOSEIRI, K. A. simulated annealing approach for the multi-periodic rail-car fleet sizing problem. Computers and Operations Research [online]. 2009, 36(6), p. 1789-1799. ISSN 0305-0548. Available from: https://doi.org/10.1016/j.cor.2008.05.004 Go to original source...
  23. VOLODARETS, M. V. Features of the AnyLogic application for solving problems of transportation simulation (in Ukrainian). In: Problems of mathematical education: challenges of the present. 2018, p. 280-283. ISBN 978-966-641-733-9
  24. BAUER, V., BAZANOV, A., KOZIN, E., NEMKOV, V., MUKHORTOV, A. Optimization of technological transport sets using AnyLogic simulation environment. Journal of Mechanical Engineering Research and Developments [online]. 2019, 42(2), p. 41-43. ISSN 1024-1752. Available from: https://doi.org/10.26480/jmerd.02.2019.41.43 Go to original source...
  25. LIPENKOV, A., KUZMIN, N. The determination of acceptable intensity level of movement of city buses in accordance with carrying capacity of a bus stop. Intellect, Innovatsii, Investicii. 2015, 3, 97102. ISSN 2077-7175.
  26. MURAVEV, D., HU, H., RAKHMANGULOV, A., MISHKUROV, P. Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: case study on the Ningbo-Zhoushan Port. International Journal of Information Management [online]. 2021, 57, p. 102-133. ISSN 0268-4012. Available from: https://doi.org/10.1016/j.ijinfomgt.2020.102133 Go to original source...
  27. COMAN, M., BADEA, D. The vehicles traffic flow optimization in an urban transportation system by using simulation modeling. Land Forces Academy Review [online]. 2017, 22, p. 190-197. eISSN 2247-840X. Available from: https://doi.org/10.1515/raft-2017-0026 Go to original source...
  28. ZHANG, Y., WANG, Y., WU, L. Research on demand-driven leagile supply chain operation model: a simulation based on AnyLogic in system engineering. System Engineering Procedia [online]. 2012, 3, p. 249-258. ISSN 2211-3819. Available from: https://doi.org/10.1016/j.sepro.2011.11.027 Go to original source...
  29. BANNIKOV, D., SIRINA, N. Model of passenger rolling stock maintenance. In: 10th International Scientific and Technical Conference Polytransport Systems: proceedings. 2018. p. 1-7.
  30. FERRARI, A., ZENEZINI, G., CARLIN, A., RAFELE, C. An integrated simulation modelling approach for a warehouse 4.0 [online]. Available from: https://doi.org/10.21203/rs.3.rs-317679/v1 Go to original source...
  31. UTOMO, D. S., GRIPTON, A., GREENING, P. Modelling home grocery delivery using electric vehicles: preliminary results of an agent-based simulation study. In: 2019 Winter Simulation Conference: proceedings. IEEE. 2019. ISBN 978-1-7281-3283-9, p. 1637-1648. Available from: https://www.informs-sim.org/wsc19papers/164.pdf Go to original source...
  32. Process modeling library blocks - The AnyLogic Company[online] [accessed 2021-03-23]. Available from: https://help.anylogic.com/index.jsp?topic=%2Fcom.anylogic.help%2Fhtml%2Fprocessmodeling%2Fcustom-block.htm

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