Abstract: The subject of the present research article is the development and practical implementation of the intelligent decision support system that distributes tasks related to maintenance of the personal data processors register. The object of the research is the task of a rational choice of task performers in the system of electronic flow of documents run by the territorial body of the Federal Supervision Agency for Information Technologies and Communications. The authors examine tasks of defending the rights of personal data owners, scheme for processing and distributing these tasks of keeping the registry of personal data processors, analyze the problem of manual distribution of tasks and set a goal to automate an efficient distribution of tasks between performers. To achieve the research target, the authors offer their own fuzzy-production model that has been developed especially for these purposes. This model allows to rationally distribute tasks of different difficulty levels based on the expert evaluation of competence, working capacity and work load of performers. The authors also give a description of the decision support system and algorithm for using it in the process of tasks distribution. The scientific novelty of the authors' approach to achieving the aforesaid goal is caused by the fact that they offer an automated distribution of tasks between performers based on developing and practically implementing the fuzzy-production model. They also provide original fuzzy-production rules to formalize expert knowledge concerning a rational selection of tasks performers taking into account their competence, working capacity and current work load. Analysis of the adequacy of this fuzzy-production model as well as efficient solution of the set goals based on the developed system has proved that it is possible to considerably decrease the intellectual load of an expert in the process of tasks distribution as well as increase the speed of the decision making process by 80.3 percent. 

Abstract: The subject of the study is to evaluate the effectiveness of assigning tasks in the automated systems of electronic document management on the basis of fuzzy methods of rational choice of alternatives. The object of the research is the problem of a rational choice of employee for the task based on qualifications, performance, workload as well as difficulty of the assignment. The paper focuses on three job assignment strategies:  based on the method of maximin convolution, additive convolutions and fuzzy-production model. Particular attention is paid to the software developed on the basis of the proposed methods. The authors present an example of its operation, as well as the results of studies evaluating the effectiveness of allocation tasks for the performers. As the methods of research authors used methods of fuzzy rational choice of alternatives: maximin convolution, additive convolutions and fuzzy-production model. These methods are used to assign tasks the automated systems of electronic document management. The main conclusions of the study are:
-          method based on fuzzy logic inference has shown the best results, most closely consistent with the intuitive representation of an expert on rational choice assignments performers;
-          maximin convolution method is a pessimistic approach, that does not take into account the good side of the alternatives;
-          method of additive convolution is an optimistic approach in which low scores on the criteria have the same weight as compared to the high marks that affected its low accuracy.
A special contribution to the authors of the study is in developing an effective fuzzy-productions tasks assignment model as well as the implementation of the software system for performing the necessary calculations to evaluate its effectiveness. This determines the scientific novelty and practical value of the study.