This research develops a method for synthesizing linguistic models of fuzzy systems with fuzzy input and output parameters that are described by linguistic variables. Based on the proposed method, linguistic models of the Title 1000 catalytic cracking unit for heavy residues at the Shymkent oil refinery are developed, describing the dependence of the volume and quality of gasoline on the input and operating parameters of the facility, which are fuzzy. It is substantiated that the use of a fuzzy approach, which allows the use of the experience, knowledge, and intuition (intelligence) of the decision maker and subject matter experts, is the most suitable effective method for synthesizing models of complex, fuzzily described objects and processes for comparison with other methods. The main idea of the proposed work is to solve the problems of shortage and fuzziness of initial information when developing models and optimizing the operating modes of a catalytic cracking unit through the use of knowledge, experience, and intuition of experts in this field. To solve the problems of the shortage of initial quantitative information and the fuzziness of available information when developing mathematical models, it is proposed to systematically use statistical methods, expert assessment methods, and a heuristic method based on fuzzy logic. The scientific novelty of the research lies in the development of a method for synthesizing linguistic models in a fuzzy environment and an algorithm for its implementation, which makes it possible to describe the dependence of the fuzzy values of the object’s output parameters on its fuzzy input and operating parameters. The proposed approach allows the formalization and synthesis of models of fuzzily described objects when other methods of model development are not applicable or do not give the expected results. The results of the work were simulated in the MATLAB Fuzzy Logic Toolbox.

Many technological systems are characterized by fuzzy initial information, necessary for the development of their models, optimization and control of operating modes. Therefore, the purpose of this study is to formulate decision making problems for optimizing and controlling operating modes of such systems in a fuzzy environment and to develop methods for solving them. The developed heuristic methods of fuzzy multi-criteria decision making are based on the modification and combination of different principles of optimality. The proposed methods based on system models, knowledge and experience of the decision maker allow iterative improvement and effective decision making. On the basis of experimental–statistical methods, methods of expert evaluation, statistical and fuzzy models of the stabilization column have been developed. The conditions for judging the fuzzy model’s effectiveness are determined and investigated. Using the proposed heuristic method based on the main criterion and maximin, the problem of two-criterion optimization of the stabilization column parameters in a fuzzy environment is solved. The results obtained confirm the advantages of the proposed method of fuzzy decision making in comparison with the results of known methods. The developed heuristic methods differ from known ones because they allow making adequate decisions in a fuzzy environment by maximizing the use of the collected fuzzy information.

The relevance of the research is caused by the need to solve effectively the problems of controlling the operating modes of chemical-technological systems, which are multi-criteria, characterized by the uncertainty and fuzziness of the initial information. Since real chemical-technological systems in production are multi-criteria and often work in the conditions of unclear initial information, formalization and effective solution of such problems in a fuzzy environment is very important and relevant for science and production. The main aim of the research is to develop a method for constructing mathematical models of chemical-technological systems based on available information of various kinds (theoretical, statistical, expert, fuzzy information); get multicriteria optimization problem statement to control such systems and develop a heuristic approach to its solution; also, to test the results obtained in practice for construction of mathematical models of chemical-technological system for benzene production and the control modes of its operation in a fuzzy environment. Objects: complex chemical-technological systems with the example of a technological plant for production of benzene, which are described by a vector of criteria and characterized by unclear initial information. Methods: methods of system analysis and fuzzy sets theories, methods of mathematical modeling and multi-criteria choice, experimental statistical methods for developing mathematical models. Results. The authors have proposed the method for developing mathematical models of chemical-technological systems based on available information of various types, including initial fuzzy information. The new tasks of control of the chemical technological systems in the conditions of fuzziness of the initial information obtained by modifications of various compromise schemes for working in a fuzzy environment. The tasks of multicriteria optimization in controlling technological system are reduced to multicriteria problems of fuzzy mathematical programming and based on modifying the principles of maximin and Pareto optimality, heuristic algorithm for solving the formulated problem of optimal control is developed. These results are realized in practice in constructing mathematical models of the main aggregates of the chemical-technological system for production of benzene and in setting and solving the task of controlling the operating modes of this system in a fuzzy environment. Analysis and comparison of the obtained results allow drawing a conclusion about the effectiveness of the proposed approach to solving control problems on the basis of models in conditions of indistinct initial information.

Many modern technological objects in practice are characterized by the uncertainty of the initial information necessary for their management. Recently, one of the pressing scientific and practical problems is the development of new optimization methods for controlling the operating modes of such objects in a fuzzy environment. In this regard, the objective of this study is to develop methods of multi-criteria optimization in a fuzzy environment by modifying the simplex method and various optimality principles based on fuzzy mathematics methods. The methodology of the proposed study is based on a hybrid approach, which consists of the integrated use and modification of simplex methods and optimization methods with various optimality principles for working in a fuzzy environment. The main results are as follows: a simplex method of multi-criteria optimization of immeasurable criteria (here, we are talking about the impossibility of physical measurements of criteria, the values of which are estimated by decision maker); a theorem on the convergence of the solution sequence obtained using the proposed method to the minimum value of the criteria; a heuristic method based on a modification for fuzziness and a combination of the maximin and Pareto optimality principles, which allows effectively solving multi-criteria optimization problems in a fuzzy environment. The heuristic method proposed will be used to solve a real production problem—optimization of the technological process of benzene production.

The monograph is devoted to the system analysis of approaches to the building of models of chemical-technological systems, on the basis of which a systematic concept of building of models and the issues of solving decision-making problems for managing the operating modes of technological objects is proposed. The problems of the development of mathematical models and the optimization of complex chemical-technological systems are investigated, using the example of technological objects of oil refining, in conditions of uncertainty caused by the lack of reliable quantitative information and the fuzziness of available information. The structure of the monograph consists of an introduction, the main part of four sections, a conclusion and a list of sources of information. In the main part of the work, the current state of the problems of mathematical modelling of technological objects of oil refining production is analyzed. Methods of mathematical modelling and decision-making in the management of technological objects according to environmental and economic criteria are chosen as the direction of research. Methods of building mathematical models of chemical-technological systems of oil refining in a fuzzy environment have been investigated and proposed, and models of the technological complex of the catalytic reforming unit have been developed. An approach to the creation of a package of models for system modelling of the technological complex of the catalytic reforming unit is described. An algorithm for the synthesis of models of a technological complex of oil refining based on fuzzy information is proposed. Expert assessments have been carried out to develop a mathematical description of the technological complex of the reforming unit, a method has been developed for carrying out expert procedures in a fuzzy environment. The formulations of decision-making problems for the control of the technological complex of the reforming unit are formulated and, based on the modification of various optimality principles, heuristic algorithms for their solution are developed. The properties of the developed algorithms for solving decision-making problems have been investigated and a method for their selection in solving specific production problems has been proposed. A mathematical formulation of the decision-making problem for optimizing the operating modes of the catalytic reforming unit in a fuzzy environment is obtained and the results of its solution based on the proposed fuzzy approach are presented. The structure is created and the main functional blocks of the computer decision support system based on the object models are described. The issues of software implementation of the developed models are considered and a description of the interface of the computer system for modelling the units of the reforming unit and decision support for optimizing their operation modes is given.

Statements of decision-making problems for the control of fuzzy technological objects are formalized and obtained, and methods for solving them are proposed. The object of study is the heating stations of the «hot» main oil pipeline. Since such objects are often characterized by multicriteria and often operate in conditions of unclear initial information, the tasks are formalized in the form of multicriteria decisionmaking problems in a fuzzy environment. Based on the modification of various optimality principles, new mathematical formulations of the problems to be solved were obtained and interactive heuristic algorithms for solving them were developed. The novelty of the proposed approaches to solving formalized fuzzy problems from well-known methods for solving fuzzy problems lies in the fact that problems are posed and solved without first converting them to equivalent deterministic options, which does not reduce the loss of original fuzzy information and makes it possible to obtain more adequate and effective solutions. An example is given of the practical application of the proposed approach to solving decision-making problems by implementing one of the developed algorithms when solving the problem of choosing an effective operating mode for the oil heating station of the Uzen-Samara oil pipeline at the Atyrau point.