Team formation based on group technology: a hybrid grouping genetic algorithm approach. (English) Zbl 1232.68099
Summary: This paper presents a new model for team formation based on group technology (TFPGT). Specifically, the model is applied as a generalization of the well-known machine-part cell formation problem, which has become a classical problem in manufacturing in the last few years. In this case, the model presented is especially well-suited for problems of team formation arising in R&D-oriented or teaching institutions. A parallel hybrid grouping genetic algorithm (HGGA) is also proposed in the paper to solve the TFPGT. The performance of the algorithm is shown in several synthetic TFPGT instances, and in a real problem: the formation of teaching groups at the Department of Signal Theory and Communications of the Universidad de Alcalá in Spain.
MSC:
| 68T05 | Learning and adaptive systems in artificial intelligence |
| 90C59 | Approximation methods and heuristics in mathematical programming |
Software:
CF-GGAReferences:
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