A Cyclic-genetic-algorithm Approach to Composing Heterogeneous Groups of Students

In this paper, the proposed model is described to demonstrate how to mix students in a heterogonous way and equally balance groups in terms of the educational background and assessment of students. A cyclic genetic algorithm (CGA) is employed in the model to mimic the natural process of evolution to achieve the optimized solution. In order to keep population diversity in the CGA, a particular cycle shift operator and self-crossover operator are presented. The model can be used as a starting point for considering both educational background and peer assessments in the formation of heterogeneous groups of students.