عنوان مقاله [English]
Humans have always sought to provide their needs and aspirations through group activities. Creating groups and teams in the past has been limited to geography and local constraints. The people whose place of residence was close together, formed the team. Gradually, along with the tendency of societies to specialization, the emergence of high-speed vehicles and communication via the Internet, overcoming the locational limitations for the team formation problem was proposed.
Choosing the best combination of experts for forming a team, has always been one of the most important issues in decision-making problems for performing research projects. In addition to being members of a team specialized in the required field, they must have a good cooperation with each other.
Researchers have developed several optimization models to minimize the number of people in the team to satisfy the required skills. However, these kinds of models do not cover the interaction problems between people. In recent years, some researchers have emphasized the importance of interactions between experts and taken into account the cost of the interaction in team formation problem, and they have solved the problem by using heuristic and meta-heuristic approaches without developing a mathematical model while the assessment quality of heuristic and meta-heuristic methods is determined based on comparison with
results of the corresponding optimization model.
In this study, a mathematical optimization model is developed for the first time to find a subset of the available expertise that fulfills the required skills with the best interactions. Because of the availability of historical data of experts' cooperation, the model tries to find members as a team that have the best cooperation with each other. In order to assess the performance of the model, a real problem and an artificial problem are presented. Results indicate the abilities of the model for problem-solving.