Modeling design information systems with multi-criteria

Abstract

This work is devoted to the development of a new method for modeling information systems of multi-criteria design, based on expert ranking of criteria. The possibilities of the fuzzy-set theory and the possibility theory allow for a comprehensive analysis of criteria by reducing numerical indicators to a qualitative form, passing to the corresponding fuzzy relations of preference. Some of the information may be lost, therefore conclusions should be applied, both on the basis of “quantitative” processing of the results of measuring the criteria, and on the basis of “qualitative” processing. If these conclusions coincide, then their adequacy will be confirmed based on the initial data. Since the modeling of complex design systems is determined by several criteria defined on different base sets, and the problem of determining the multi-criteria efficiency in conditions of incompleteness of the initial data remains relevant, within the framework of this article, an optimization method is proposed simultaneously according to many criteria with incompleteness of the initial data. The difference between the described method lies in the fact that the expert ranking of criteria enables to formally set fuzzy preference graphs that make it possible to obtain comprehensive information about estimates in the rank scale during pairwise comparisons, with the aim of subsequent search for Pareto-optimal solutions in multi-criteria problems.