Solving the problem of ranking applicants for a project team with fuzzy assessment of competencies and requirements

Abstract

The article's subject is models and methods for ranking candidates for an IT project team with uncertainty regarding competencies and requirements. The aim is to improve the quality of the IT project team by creating and applying models and a method for formalizing the task of multi-criteria ranking of candidates for the team, taking into account the uncertainty of the initial information. Tasks: to analyze the relevance of the task of creating models and methods for ranking candidates for the IT project team under conditions of uncertainty; to develop a method for multi-criteria ranking of candidates for the IT project team in a fuzzy formulation; and to solve an example of the task of multi-criteria ranking of applicants for further formation of the IT project team. The methods used are the analytic hierarchy process, the line method, and the fuzzy arithmetic method. The following results have been obtained. A method of multi-criteria ranking of candidates for an IT project team has been developed, which differs from existing methods by using fuzzy numbers to set the preferences of candidates and assess the generalized competence of each candidate based on comparisons with the reference competence, which improves the ability to evaluate candidates. This method can be used in the first stage of creating an IT project team when candidates for the team are ranked. The task of selecting candidates for further formation of the IT project team has been solved. Conclusions. The scientific novelty of the method of multi-criteria ranking of candidates for the project team is that, unlike existing methods, it uses fuzzy ideas about the preferences of candidates when assessing the generalised competence of each candidate based on comparisons with the reference competence, which allows to improve the ability to evaluate candidates. This article considers an example of using the proposed method to solve the problem of selecting candidates to further solve the problem of forming an IT project team under fuzzy evaluation.