|Affiliations:||Mathematical Institute of the Serbian Academy of Sciences and Arts||Title:||Design of balanced MBA student teams||Journal:||Journal of the Operational Research Society||Volume:||56||Issue:||1||First page:||60||Last page:||66||Issue Date:||1-Jan-2005||Rank:||M22||ISSN:||0160-5682||DOI:||10.1057/palgrave.jors.2601775||Abstract:||
In some schools and universities, students must sometimes be divided into several teams in such a way that each team provides a good representation of the classroom population. In this paper, two different ways of measuring the balance among teams are proposed: min-sum and min-max objective functions. For the first function and the Li-norm used in the space of attributes, an exact solution method based on a set partitioning formulation and on the enumeration of all possible team patterns is presented. For the second objective function, a set partitioning formulation is also considered, but as an approximation. In order to solve large problem instances, we have also developed metaheuristics based on variable neighbourhood search. Models and methods are tested on data from an MBA programme.
|Keywords:||Clustering | Metaheuristics | Set partitioning | Variable neighbourhood search||Publisher:||Taylor & Francis|
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