N.D. Ivanov – Engineer, Siberian Federal University (Krasnoyarsk)
A.I. Legalov – Dr.Sc. (Eng.), Professor, Head of Scientific and Educational Laboratory «Programming Technology»,
Siberian Federal University (Krasnoyarsk)
A.V. Ankudinov – Ph.D. (Eng.), Associate Professor, Chief Designer of OCD, JSC Academician M.F. Reshetnev Information Satellite Systems (Zheleznogorsk)
A.I. Postnikov – Ph.D. (Eng.), Associate Professor, Siberian Federal University (Krasnoyarsk)
The process of choosing the configuration of a hierarchical system is not an easy task, and the decision itself is not obvious due to the similarity of the parameters of alternative options and the presence of many conflicting criteria that are not amenable to manual analysis.
Multi-criteria analysis of complex hierarchical systems requires processing a large amount of data, which is an excessively resource-intensive process. This is mainly due to the size of the structure of the developed system, in which each subsystem is represented by its own set of alternatives of options, parameters and criteria for their evaluation. The detailed study of these subsystems is separate from each other and may not give the desired solution as a result. When forming the final decision, the top-level decision maker, as a rule, is guided by the indicators of the complete system, therefore, makes an informed choice of configuration, which includes not only the best representatives of each of the subsystems. As a result, the overall task of multi-criteria analysis is complicated by the need for additional study of the resulting structure.
The tools considered in the article cannot be effectively used to solve the problem of multicriteria analysis by a subject specialist who does not own these tools. The way out of this situation is the creation of a problem-oriented decision-making tool that implements the necessary data analysis methods and has a shell that provides tuning for the required subject area and task. The creation of such a system allows user-specialists to use existing methods of multi-criteria analysis to effectively solve their problems by pre-adjusting the system.
The overall architecture of the problem-oriented instrumental support environment of the user in multi-criteria analysis tasks was de-veloped as a set of three main levels: the subsystem tuning subsystems, the user's work subsystem, the kernel subsystem.
The presented tools provide not only carrying out the required calculations, but also pre-setting the application on the subject area, which facilitates the work of users who solve specific applied problems. The organization of the environment allows you to separate the functions of different users, to separate the setting on the subject area from the process of directly solving the problem. The in-dependence of the computational core from user interfaces allows for an evolutionary increase in the functionality of the application.
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