Fuzzy economic and mathematical models for planning of the technological systems' classes operation
DOI:
https://doi.org/10.15802/pte.v0i12.95624Keywords:
economic and mathematical modeling, classes of technical systems, operation, specialization, fuzzy mathematical development and management, two-stage planning modelAbstract
Goal. The article is dedicated to improve economic and mathematical planning models of the optimal distribution of the service orders. It shows the results of the research of the several classes of technical systems' operation, taking into account environment uncertainty. Planning models take into account the specialization of the work of performers, as well as the possibility of parameters' perturbation of production facilities and the environment, that are represented by fuzzy values. Methods. For the operation planning of several similar object classes (production and technical systems), taking into account the requirements of the work distribution based on the specialization of performers, the economic and mathematical models are formed that summarize the open model of the transport problem of the targets' distribution with limited bandwidth. The models meet the conditions of the multiproduct flows' functioning. The coefficients of the matrix of unit costs and limited resource settings are fuzzy values. Results. This article shows the improved economic and mathematical models of analysis and planning processes of several classes of industrial and technical systems' operation that provide the possibility of the fuzzy description of parameters and conditions. The models take into account both the current state of the technical systems and the possible perturbations of operation processes. Scientific novelty. New economic and mathematical planning models of processes operating inhomogeneous classes of technical systems have been developed. They take into account the requirements for spectators' specialization, as well as the possibility of the fuzzy description of the system parameters. Practical significance. The research results provide opportunities to improve the operational efficiency of inhomogeneous technical systems processing, as well as automated planning of resource allocation between the performers, taking into account the specialization, fuzzy parameters and the environment disturbances.
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