Multigroup Multirole Assignment

Role-based collaboration (RBC) theory is a promising paradigm for problem-solving in complex systems. Multigroup role assignment (MGRA) specifically tackles the task of assigning roles for multigroup collaboration. However, due to the constraint that an agent can only play a role in one group, the current MGRA models are incapable of handling when required agents outnumber the available supply. Group multirole assignment (GMRA) resolves the problem by permitting an agent to be assigned multiple roles, but it cannot address the assignment involving multiple environments-classes, agents, roles, groups, objects (E-CARGO) groups. Therefore, this article presents a comprehensive overview of the GMRA problem in multiple E-CARGO groups under various conditions, generalized as the multigroup multirole assignment (MGMRA) problem. The MGMRA problem primarily revolves around two key factors: the maximum number of roles that an agent can undertake within an E-CARGO group, and the maximum number of different roles across all E-CARGO groups, which have a significant impact on the sufficiency or necessity conditions of the algorithm as well as its performance. Therefore, a unified model and its special cases are proposed to solve the concrete assignment problems under different conditions. The effectiveness of models is verified through comprehensive experiments.