Svir-M, selection and ranking alternatives system: theoretical foundations and practice of application

The article examines upper-level decision-making systems that involve selecting from a finite set of alternatives, known as multidimensional object assessment systems. Examples of such systems are provided. Given the general impossibility of establishing a complete and strict order on a finite set of alternatives using logical methods alone, we offer a theoretical justification for the universality of these systems, which integrate both logical and computational methods for multidimensional evaluation. The work presents the axioms that underpin the development of logical and computational models for multidimensional object assessment. By applying system analysis principles for selecting entities based on multiple indicators from a finite set of alternatives, we establish connections between multidimensional ordering and classification methods, as well as within groups of these methods. These connections are represented in a task tree of the updated SVIR-M selection and ranking system. The principles of this system, consisting of nine programs tailored to specific tasks, are outlined. In the problem setup interface, a task tree of multidimensional object assessment is modeled. SVIR-M's initial data comprises a finite set of objects, each characterized by a set of indicators and requirements. Data preparation involves group preparation using MS Excel and individual preparation through system tools. The multidimensional object assessment model developed within the system can address various problems. Examples of practical applications of the system are provided.