Proposing a mathematical model for selection team member in R&D teams and solving it using Multi-Objective Simulated Annealing (Case study: Keyson Company)

Today, the necessity of forming teams has become more important than ever and firms begin to concentrate on finding proper people with team skills. This is especially true in research and development (R&D) organizations that are critical for maintaining organizational innovation. Organizations rely on R&D teams to develop new technologies and products. Thus, the aim of this research is to select the best individuals as R&D team members. So far, several methods have been used to select members and mathematical modeling has been considered as an efficient approach. This research is an applied and descriptive – analytical research. For this purpose, the objective function is to choose individuals who earn the most points and decision variable is 0-1 if the candidate is selected or not. Individual characteristics of team members are derived from existing competency models. Individual weights will be obtained by using revised Simos and according to experts and Myers-Briggs Type Indicator will be employed to gain collaborative weights. Finally, Multi Objective Simulated Annealing algorithm will be used to solve the problem. The modeling was used for team member selection of one of the largest Keyson Company R&D projects.