Group Role Assignment via a Kuhn-Munkres Algorithm-Based Solution

• Published in: IEEE transactions on systems, man and cybernetics. Part A, Systems and humans Vol. 42; no. 3; pp. 739 - 750
• Main Authors: Haibin Zhu, MengChu Zhou, Alkins, R.
• Format: Journal Article
• Language: English
• Published: IEEE 01.05.2012
• Subjects: Algorithm; Algorithm design and analysis; assignment problem; Collaboration; Complexity theory; Educational institutions; group role assignment; Humans; role; Role transfer; Vectors
• ISSN: 1083-4427; 1558-2426
• DOI: 10.1109/TSMCA.2011.2170414

Role assignment is a critical task in role-based collaboration. It has three steps, i.e., agent evaluation, group role assignment, and role transfer, where group role assignment is a time-consuming process. This paper clarifies the group role assignment problem (GRAP), describes a general assignment problem (GAP), converts a GRAP to a GAP, proposes an efficient algorithm based on the Kuhn-Munkres (K-M) algorithm, conducts numerical experiments, and analyzes the solutions' performances. The results show that the proposed algorithm significantly improves the algorithm based on exhaustive search. The major contributions of this paper include formally defining the GRAPs, giving a general efficient solution for them, and expanding the application scope of the K-M algorithm. This paper offers an efficient enough solution based on the K-M algorithm that outperforms significantly the exhaustive search approach.