Abstract:
Technological objects and processes are often characterized by fuzzy initial information
necessary for developing their models and optimization. The purpose of the study is to develop
a method for synthesizing linguistic models of fuzzy described objects and a heuristic method
for solving the multicriteria optimization problem in a fuzzy environment. Based on the expert
assessments and logical rules of conditional inference, a method for synthesizing linguistic models
was developed for describing processes with fuzzy input and output parameters. To solve the
problem of multicriteria optimization, a heuristic method based on the modification and combination
of various optimality principles is proposed. Coking reactor models were developed by modifying
the successive regression inclusion method and the least squares method. Linguistic models of the
delayed coking process were developed in the Fuzzy Logic Toolbox, allowing to evaluate the coke
quality depending on the temperature and pressure of coking reactors. Using the proposed heuristic
method, the problem of two-criteria optimization of the delayed coking process with fuzzy constraints
is solved. The results confirm the advantages of the proposed fuzzy approach compared with the
well-known approaches. Unlike them, the proposed method allows making adequate decisions in a
fuzzy environment by maximizing the use of available fuzzy information.
