Abstract
This paper presents the problem of controlling the transportation of cargo in the mechanical transport system. The overall efficiency of the system includes the costs of reconfiguration, involving both software and manual changes in the parameters and relationships of equipment components. The decision-making phase about choosing the reconfiguration method is preceded by the analysis of the utility of possible methods. The complexity of the solution of the considered problem consists in the ambiguous estimation of the network state due to the considerable number of parameters and incompleteness of information about their values. Except the status, the reconfiguration effect depends on the dynamics of the input flows and the effect of the external environment on the network after reconfiguration. The way of the solution of the problem, based on the image representation of the reconfiguration experience, is considered. The model of the image representation of knowledge and reasoning on their basis is described. The advantage of model of representation of precedents of reconfiguring by images is analyzed. The example of the image representation of situations reflecting the set of knowledge about the input flow, the degree of congestion of the subnet, and the forecast of the behavior of the reconfigured network is given. The boundaries of application of the proposed method are analyzed.
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Acknowledgment
This work has been supported by the Council for Grants (under RF President) and State Aid of Leading Scientific Schools (grant MK-521.2017.8).
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Belyakov, S., Savelyeva, M. (2019). Intelligent Method of Reconfiguring the Mechanical Transport System. In: Silhavy, R. (eds) Software Engineering and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 763. Springer, Cham. https://doi.org/10.1007/978-3-319-91186-1_18
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DOI: https://doi.org/10.1007/978-3-319-91186-1_18
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