Open AccessImprovement of Algorithms and Procedures of Decision Support in the Field of Personnel Management
Author(s) -
Iryna Davydova,
Oleksandr Balan,
Olena Danyliuk,
Maryna Horbashevska,
Nataliia Bakulina,
Illia Samarchenko
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d7705.118419
Subject(s) - ambiguity , field (mathematics) , human resource management , computer science , position (finance) , human resources , resource (disambiguation) , decision support system , selection (genetic algorithm) , management science , human resource management system , fuzzy logic , risk analysis (engineering) , operations research , knowledge management , business , artificial intelligence , engineering , mathematics , management , economics , computer network , finance , pure mathematics , programming language
In current conditions, the staff is considered as the leading resource of the organization. The theory that defines personnel as costs, which, above all, should be reduced, has been replaced by the theory of human resource management. Under this theory, the staff is one of the primary resources of the organization that must be properly managed, create optimal conditions for its development, and invest the necessary funds in this. The problem of selecting personnel for a position belongs to the category of loosely structured tasks that traditionally boil down to decision making. That is why the challenge of improving the algorithms and procedures for decision support in the field of personnel management is very relevant in the modern world. The article substantiates the need to use intelligent technologies to support decision-making in human resource management tasks. The specific features of the personnel selection problem are highlighted, immersing the latter in a fuzzy environment. A multi-scenario approach is described for solving the problem of hiring, which takes into account the importance and ambiguity of indicators characterizing applicants for the position, as well as the nature of the requirements of employers.