A new algorithm to create balanced teams promoting more diversity

ABSTRACT

The problem of assigning students to teams can be described as maximising their profiles diversity within teams while minimising the differences among teams. This problem is commonly known as the maximally diverse grouping problem and it is usually formulated as maximising the sum of the pairwise distances among students within teams. We propose an alternative algorithm in which the within group heterogeneity is measured by the attributes' variance instead of by the sum of distances between group members. The proposed algorithm is evaluated by means of two real data sets and the results suggest that it induces better solutions according to two independent evaluation criteria, the Davies–Bouldin index and the number of dominated teams. In conclusion, the results show that it is more adequate to use the attributes' variance to measure the heterogeneity of profiles within the teams and the homogeneity among teams.

KEYWORDS:

• Team formation
• team roles
• student diversity

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Teresa Galvão Dias has a background in Mathematics and holds a PhD in Sciences of Engineering (University of Porto, Portugal). She is Assistant Professor in the Faculty of Engineering of University of Porto. She is involved in lecturing Information Systems, Operations Research and Human Computer Interaction courses. She has actively participated in several large national and European R&D projects in areas such as decision support systems, transportation systems and mobility. Her main research interests are combinatorial optimization problems, metaheuristics, human-computer interaction and transportations systems and he regular publishes papers in International Scientific Journals.

José Borges received his PhD in Computer Science from University College of London, an MSc in Electrical Engineering and Computer Science and a first degree in Mechanical Engineering, both from University of Porto. He is currently an Assistant Professor and Researcher at the Department of Industrial Engineering and Management. He teaches courses in Statistics, Data Mining, Information Systems and Human Computer Interaction. His research interests include web data mining, data analysis and data science, information visualization and teamwork analysis. He has published 25+ papers in International Journals, ISI proceedings and book chapters.