TY - JOUR
T1 - Group role assignment via a Kuhn-Munkres algorithm-based solution
AU - Zhu, Haibin
AU - Zhou, Mengchu
AU - Alkins, Rob
N1 - Funding Information:
Manuscript received March 24, 2010; revised October 4, 2010 and April 3, 2011; accepted August 6, 2011. Date of publication November 18, 2011; date of current version April 13, 2012. This work was supported in part by the National Sciences and Engineering Research Council of Canada (No. 262075-06), by an IBM Eclipse Innovation Grant, by the National Natural Science Foundation of China under Grant 61034004, and by the National Basic Research Program of China under Grant 2011CB302804. This paper was recommended by Associate Editor A. Bargiela.
PY - 2012/5
Y1 - 2012/5
N2 - 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.
AB - 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.
KW - Algorithm
KW - assignment problem
KW - group role assignment
KW - role
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U2 - 10.1109/TSMCA.2011.2170414
DO - 10.1109/TSMCA.2011.2170414
M3 - Article
AN - SCOPUS:84860161434
SN - 1083-4427
VL - 42
SP - 739
EP - 750
JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
IS - 3
M1 - 6084856
ER -