Assessment of Cargo Delivery Quality Using Fuzzy Set Apparatus

  • Authors

    • Hanna Kyrychenko
    • Yurii Statyvka
    • Oleh Strelko
    • Yulia Berdnychenko
    • KHalyna Nesterenko
    2018-09-15
    https://doi.org/10.14419/ijet.v7i4.3.19800
  • assessment of cargo delivery quality, method of making control-time points, model goods delivery processes, prognosis deviation, scale of values.

  • Abstract

    The influence of the existing operation conditions for the time of cargo transportation, i.e. ferrous metals to the port station, was investigated. It was proposed to carry out the management of cargo delivery on the basis of determining the values of cargo handling duration while implementing the stages of the schedule. It was proposed to carry out assessment of the delivery process, including transportation using the fuzzy set apparatus. To determine the quality of transportation, an ordered categorized scale of values of the duration of cargo's staying in certain conditions at delivery stages was proposed. The assessment of deviations at all the stages of transportation with the use of linguistic definitions of conditions allows quantifying such an indicator as the transportation quality. The characteristics of deviations during transportation are provided in the linguistic form to the dispatching unit for making a decision. The revealed regularities in deviations from the standard schedules of trains during delivery of cargos are an objective basis for taking into account them in the mathematical models of the forecast of time of cargo delivery at each of the defined stages of transportation. The data on the forecasted and actual transportations are accumulated in the existing information base, forming data files for assessing the quality of the transportation process, the adequacy of the mathematical model and correcting of the model in case of significant organizational or technical changes.

     

  • References

    1. [1] D. Adebanjo, An investigation of the adoption and implementation of benchmarking, International Journal of Operations & Production Management, Vol.30, No.11, (2010), pp. 1140-1169.

      [2] D. Lomotko, E. Alyoshinsky, G. Zambrybor, Methodological Aspect of the Logistics Technologies Formation in Reforming Processes on the Railways, Transportation Research Procedia, Vol.14, (2016), pp. 2762-2766.

      [3] J. Gou, T. Ma, J. Li, A research on Supply Chain Integration Strateg Based on Virtual Value Net, Research and Practical Issues of Enterprise Information Systems II, Vol.2, (2007), pp. 887-891.

      [4] A. Nagurney, D. Li, Competing on Supply Chain Quality: A Network Economics Perspective, Springer International Publishing, (2016).

      [5] P. Brandimarte, G. Zotteri, Introduction to distribution logistics, Wiley, NY, (2007).

      [6] D. Teodorovic, M. Janic, Transportation Engineering: Theory, Practice and Modeling, Butterworth-Heinemann, (2016).

      [7] T. Pohja, Some theoretical foundations of Supply Chain Management and Supply Networks: the role of social networks in selecting partners. The paper was published at the 20th IMP-conference in Copenhagen, Denmark, (2004).

      [8] H. Min, G. Zhou, Supply chain modeling: past, present and future, Computers and Industrial Engineering – Supply chain management, Vol.43, (2002), pp. 231-249.

      [9] Dr. Rajagopal, Systems Thinking and Process Dynamics for Marketing Systems: Technologies and Applications for Decision Management. Monterrey Institute of Technology and Higher Education ITESM, Mexico, (2012).

      [10] H. Karimi, N. Duffie, M. Freitag, M. Lütjen, M. Chadli, Modeling Planning, and Control of Complex Logistic Processes, Mathematical Problems in Engineering, No.501, (2015), pp. 184267.

      [11] T. Butko, A. Prokhorchenko, M. Muzykin, An improved method of determining the schemes of locomotive circulation with regard to the technological peculiarities of railcar traffic, Eastern-European Journal of Enterprise Technologies, No.5(3), (2016), pp. 47-55.

      [12] V. Skalozub, O. Ivanov, O. Shvets, Nechitki modeli upravlinnia ekspluatatsiieiu tekhnichnykh system dlia zabezpechennia stiikosti zaliznychnykh perevezen, Transport systems and transportation technologies, Vol.9, (2015), pp. 65-71.

      [13] G. Kirichenko, S. Ovcharenko, Development of the method of control points for controlling delivery schedules, Transport problems, Vol.10, (2014), pp. 112-118.

      [14] H. Kyrychenko, Applying processes modelling to manage goods delivery, III International Scientific and Practical Conference «Modern Scientific Achievements and Their Practical Application», Vol.1, No.5(21), (2017), pp. 53-55.

      [15] L. Riza, F. Herrera, C. Bergmeir, J. Benitez, Frbs: Fuzzy Rule-Based Systems for Classification and Regression, Journal of Statistical Software, Vol. 65(6), (2015), pp. 1-8.

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  • How to Cite

    Kyrychenko, H., Statyvka, Y., Strelko, O., Berdnychenko, Y., & Nesterenko, K. (2018). Assessment of Cargo Delivery Quality Using Fuzzy Set Apparatus. International Journal of Engineering & Technology, 7(4.3), 262-265. https://doi.org/10.14419/ijet.v7i4.3.19800

    Received date: 2018-09-18

    Accepted date: 2018-09-18

    Published date: 2018-09-15