Development of a model for international cargo delivery process

Authors

DOI:

https://doi.org/10.15587/2312-8372.2015.47954

Keywords:

international cargo delivery, mathematical model, Markov’s chains, regression analisys

Abstract

In the conditions of growing level of competition and transportation volumes, the task of the assessment of demand parameters impact on carriers expenses becomes particular important when choosing the optimal technological schemes. At the same time the random nature of the transportation process and the limitations imposed by existing laws and acts regulating international road transport should be taken into account in the mathematical model. Existing methods of rationalization of cargo delivery process have some disadvantages due to which their use in the conditions of transport enterprises at the contemporary market is inefficient. The majority of existing methods and models for rationalization of the delivery schemes do not consider the probabilistic characteristics of transport process parameters, and that reduces the efficiency of managerial and organizational decisions. The proposed mathematical models allow us to take into account the random nature of the process of international cargo delivery, if the appropriate statistical data on time parameters and speed of the vehicle are available. Proposed approach allows defining the impact of stochastic demand parameters on operating costs of the transport firm and, as a result, – choosing the appropriate rational schemes of transport servicing.

Author Biography

Vitalii Naumov, Kharkiv National Automobile and Highway University, 25 Petrovskogo str., Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Professor

Department of Transportation Technologies

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Published

2015-07-23

How to Cite

Naumov, V. (2015). Development of a model for international cargo delivery process. Technology Audit and Production Reserves, 4(3(24), 33–36. https://doi.org/10.15587/2312-8372.2015.47954

Issue

Section

Systems and Control Processes: Original Research