Multi-Objective Optimization based on Role in Mentorship Mode

In this paper, we propose a Multi-Objective Optimization problem with Mentorship Mode (MM-MOOP) and formalize the real-world collaboration problem using group role assignment (GRA) framework. The GRA with budget constraints, which is a typical Multi-Objective Nonlinear Optimization problem, and it can be transformed into linear optimization problems and solved by IBM ILOG CPLEX optimization package (CPLEX). Through simulation experiment, the optimal proportion of novice and veteran in the group is obtained. The experiments also verifie that the group performance in Mentorship Mode can be improved under the same budget constraints.