Extension of TOPSIS Method for R&D Personnel Selection Problem with Interval Grey Number

R&D personnel selection is a multi-attribute decisionmaking (MADM) problem. This paper develops an approach based on the technique for order performance by similarity to ideal solution (TOPSIS), to help the decision makers choose optimal R&D personnel in an uncertain environment. Grey theory is one of the methods used to study uncertainty, being superior in the mathematical analysis of systems with uncertain information. For this, the paper aims to extend the TOPSIS with grey theory. Firstly, the rating of each alternative and the weight of each criterion are described by linguistic terms which can be expressed in interval grey numbers. Then, a relative closeness is defined to determine the ranking order of all alternatives by calculating the grey relational grade (GRG) of each alternative to the ideal and negative ideal solution simultaneously.