Formalising the formation of project teams considering alternative competence assessments under uncertainty - Igor Kononenko; Oksana Kononenko; Igbal Babayev Alican; Rasim Abdullayev Soltanaga (Радіоелектронні і комп'ютерні системи)
The subject of this paper is mathematical models and methods of project team formation under conditions of uncertainty regarding candidates’ competences and requirements. The aim is to create an approach to formalising project team formation that considers multiple fuzzy assessments of specific candidate qualities. Tasks to be solved: to define a way of describing a set of fuzzy evaluations of specific qualities of candidates, to define a way of checking whether the candidate's qualities meet the fuzzy requirements, to propose a mathematical model of the problem, and to solve a test case. The methods used are: fuzzy set theory, multicriteria optimisation methods. The following results were obtained: it was proposed to use a trapezoidal fuzzy interval to describe the set of evaluations of specific candidate properties; to determine the compliance of candidate properties with fuzzy requirements, it was proposed to calculate the value of the requirements membership function at the point equal to the lower modal value of the fuzzy interval describing candidate properties; an example of applying the approach to solving the problem of forming a project team is considered. Conclusions. Because of the research conducted, it was proposed to describe multiple evaluations of a particular candidate property using trapezoidal fuzzy intervals. The novelty of the proposed approach lies in the method for evaluating the conformity of a set of assessments of a candidate’s qualities with fuzzy requirements. It is proposed to form a project team by maximising the sum of dominant competencies and the weighted sum of competencies, subject to constraints on the workload of the work, on the fulfilment of competency requirements and on the cost of the team’s work.  The generalised function method was applied to solve the multi-criteria problem.