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Author: search.filters.author.Khalid, BilalSubject: search.filters.subject.Commerce

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    Item type:Publication,
    Predictive methodology for assessing periodic market fluctuations
    (2021-01-01)
    Sergeev, S. M.
    ;
    Barykin, S. E.
    ;
    Burova, A. Yu
    ;
    Borisoglebskaya, L. N.
    ;
    Buniak, V. L.
    The paper presents the results of developing algorithms aimed at optimizing managerial decision-making in commerce. The most difficult task in constructing algorithms for supporting managerial decisions within the Industry 4.0 paradigm is to develop an interface for machine-to-machine interaction between data flows describing the current market demand and software-controlled subsystems of digital logistics platforms. Several problems have to be solved, taking into account diverse criteria. We used methods of stochastic mathematical modeling, queuing theory and the theory of optimal decisions, proposing a procedure for assessing periodic movements of consumer demand with uncertain dynamics of market indicators. A convenient implementation is offered in the form of software for digital logistics platforms, relevant for a wide range of business applications.
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    Stochastic algorithms for managing the flows of material resources of a logistics hub
    (2021-01-01)
    Provotorov, V. V.
    ;
    Barykin, S. E.
    ;
    Ostrovskaya, N. V.
    ;
    Volkova, E. S.
    ;
    Khalid, Bilal
    Digital logistics platforms have already become a major trend in the recent years, making dramatic advances during the COVID-19 pandemic. The architecture of modern logistics industry exhibits a tendency towards consolidation of commerce into networks. Making decisions in such a business environment is difficult due to imperfect algorithms, which is the main obstacle to increasing the economic feasibility of logisitcs. This study considers the development of an algorithmic basis for the software shell of the control server processing the flow of data on the movement of goods and cargo through a network. Because it is more profitable to use two-stage rather than single-stage nodes for intermediate storage and processing in modern commercial networks, the mathematical model should reflect the complex structure of such a logistics hub. The algorithms were developed acccounting for the stochastic nature of the flows of goods and cargo due to the market uncertainty of the operating conditions of the logistics hub.