Аннотации:
The study and solution of breakdowns that arise in the decision-making
process to control the operating modes of complex, fuzzy chemical-technological
systems, such as a reformer, based on their models, is currently one of the topical issues
of science and practice. To develop mathematical models of such systems characterized
by a lack and fuzziness of the initial information and to solve decision-making problems
in the process of controlling their operation modes, it becomes necessary to apply a
systematic approach that allows the complex use of statistical methods, expert assessments
and methods of fuzzy set theory. In this paper, on the example of a reforming unit of
a catalytic reforming unit, the actual problems of complex systems characterized by a
deficit and fuzzy initial information are investigated and effective methods for solving
them are proposed. On the basis of a systematic approach, a technique for developing
mathematical models of complex technological systems characterized by a lack of
quantitative information and the fuzziness of available information is proposed. The
proposed method allows solving the problems of synthesizing complex object models
under conditions of uncertainty using available data and information of various nature.
A block diagram of the decision-making process has been created and described. A
mathematical statement of the problem of choosing an effective operating mode of the
reforming unit in a fuzzy information environment is formalized and obtained in the
form of a problem of fuzzy mathematical programming. Based on the methodology of
system analysis, a new, effective method for developing models of objects characterized
by a lack of quantitative data and fuzzy initial information is proposed, using the
available information of a different nature. The formulation of the decision-making
problem under conditions of fuzziness and the heuristic approach to its solution are based on the modification of the combination of the principles of optimality of the main
criterion and maximin.
